A Cortical Mechanism Linking Saliency Detection and Motor Reactivity in Rhesus Monkeys.

Sudden and surprising sensory events trigger neural processes that swiftly adjust behavior. To study the phylogenesis and the mechanism of this phenomenon, we trained two male rhesus monkeys to keep a cursor inside a visual target by exerting force on an isometric joystick. We examined the effect of surprising auditory stimuli on exerted force, scalp electroencephalographic (EEG) activity, and local field potentials (LFPs) recorded from the dorsolateral prefrontal cortex. Auditory stimuli elicited (1) a biphasic modulation of isometric force, a transient decrease followed by a corrective tonic increase, and (2) EEG and LFP deflections dominated by two large negative-positive waves (N70 and P130). The EEG potential was symmetrical and maximal at the scalp vertex, highly reminiscent of the human "vertex potential." Electrocortical potentials and force were tightly coupled: the P130 amplitude predicted the magnitude of the corrective force increase, particularly in the LFPs recorded from deep rather than superficial cortical layers. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to salient sensory events.Significance Statement Survival in the natural world depends on an animal's capacity to adapt ongoing behavior to abrupt unexpected events. To study the neural mechanisms underlying this capacity, we trained monkeys to apply constant force on a joystick while we recorded their brain activity from the scalp and the prefrontal cortex contralateral to the hand holding the joystick. Unexpected auditory stimuli elicited a biphasic force modulation: a transient reduction followed by a corrective adjustment. The same stimuli also elicited EEG and LFP responses, dominated by a biphasic wave that predicted the magnitude of the behavioral adjustment. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to unexpected events.

Risk-Taking Is Associated with Decreased Subjective Value Signals and Increased Prediction Error Signals in the Hot Columbia Card Task.

It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.

Belief Updating during Social Interactions: Neural Dynamics and Causal Role of Dorsomedial Prefrontal Cortex.

In competitive interactions, humans have to flexibly update their beliefs about another person's intentions in order to adjust their own choice strategy, such as when believing that the other may exploit their cooperativeness. Here we investigate both the neural dynamics and the causal neural substrate of belief updating processes in humans. We used an adapted prisoner's dilemma game in which participants explicitly predicted the coplayer's actions, which allowed us to quantify the prediction error between expected and actual behavior. First, in an EEG experiment, we found a stronger medial frontal negativity (MFN) for negative than positive prediction errors, suggesting that this medial frontal ERP component may encode unexpected defection of the coplayer. The MFN also predicted subsequent belief updating after negative prediction errors. In a second experiment, we used transcranial magnetic stimulation (TMS) to investigate whether the dorsomedial prefrontal cortex (dmPFC) causally implements belief updating after unexpected outcomes. Our results show that dmPFC TMS impaired belief updating and strategic behavioral adjustments after negative prediction errors. Taken together, our findings reveal the time course of the use of prediction errors in social decisions and suggest that the dmPFC plays a crucial role in updating mental representations of others' intentions.

CDKL5-mediated developmental tuning of neuronal excitability and concomitant regulation of transcriptome.

Cyclin-dependent kinase-like 5 (CDKL5) is a serine-threonine kinase enriched in the forebrain to regulate neuronal development and function. Patients with CDKL5 deficiency disorder (CDD), a severe neurodevelopmental condition caused by mutations of CDKL5 gene, present early-onset epilepsy as the most prominent feature. However, spontaneous seizures have not been reported in mouse models of CDD, raising vital questions on the human-mouse differences and the roles of CDKL5 in early postnatal brains. Here, we firstly measured electroencephalographic (EEG) activities via a wireless telemetry system coupled with video-recording in neonatal mice. We found that mice lacking CDKL5 exhibited spontaneous epileptic EEG discharges, accompanied with increased burst activities and ictal behaviors, specifically at postnatal day 12 (P12). Intriguingly, those epileptic spikes disappeared after P14. We next performed an unbiased transcriptome profiling in the dorsal hippocampus and motor cortex of Cdkl5 null mice at different developmental timepoints, uncovering a set of age-dependent and brain region-specific alterations of gene expression in parallel with the transient display of epileptic activities. Finally, we validated multiple differentially expressed genes, such as glycine receptor alpha 2 and cholecystokinin, at the transcript or protein levels, supporting the relevance of these genes to CDKL5-regulated excitability. Our findings reveal early-onset neuronal hyperexcitability in mouse model of CDD, providing new insights into CDD etiology and potential molecular targets to ameliorate intractable neonatal epilepsy.

Cortical activations associated with spatial remapping of finger touch using EEG.

The spatial coding of tactile information is functionally essential for touch-based shape perception and motor control. However, the spatiotemporal dynamics of how tactile information is remapped from the somatotopic reference frame in the primary somatosensory cortex to the spatiotopic reference frame remains unclear. This study investigated how hand position in space or posture influences cortical somatosensory processing. Twenty-two healthy subjects received electrical stimulation to the right thumb (D1) or little finger (D5) in three position conditions: palm down on right side of the body (baseline), hand crossing the body midline (effect of position), and palm up (effect of posture). Somatosensory-evoked potentials (SEPs) were recorded using electroencephalography. One early-, two mid-, and two late-latency neurophysiological components were identified for both fingers: P50, P1, N125, P200, and N250. D1 and D5 showed different cortical activation patterns: compared with baseline, the crossing condition showed significant clustering at P1 for D1, and at P50 and N125 for D5; the change in posture showed a significant cluster at N125 for D5. Clusters predominated at centro-parietal electrodes. These results suggest that tactile remapping of fingers after electrical stimulation occurs around 100-125 ms in the parietal cortex.

Top-down and bottom-up oscillatory dynamics regulate implicit visuomotor sequence learning.

Implicit visuomotor sequence learning is crucial for acquiring skills that result in automated behaviors. The oscillatory dynamics underpinning this learning process are not well understood. To address this gap, the current study employed electroencephalography with a medium-density array (64 electrodes) to investigate oscillatory activity associated with implicit visuomotor sequence learning in the Serial Reaction Time task. In the task, participants unknowingly learn a series of finger movements. Eighty-five healthy adults participated in the study. Analyses revealed that theta activity at the vertex and alpha/beta activity over the motor areas decreased over the course of learning. No associations between alpha/beta and theta power were observed. These findings are interpreted within a dual-process framework: midline theta activity is posited to regulate top-down attentional processes, whereas beta activity from motor areas underlies the bottom-up encoding of sensory information from movement. From this model, we suggest that during implicit visuomotor sequence learning, top-down processes become disengaged (indicated by a reduction in theta activity), and modality specific bottom-up processes encode the motor sequence (indicated by a reduction in alpha/beta activity).

Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex.

We currently lack a reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC). We recently found that the strength of early and local dlPFC transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely across dlPFC subregions. Despite these differences in response amplitude, reliability at each target is unknown. Here we quantified within-session reliability of dlPFC EL-TEPs after TMS to six left dlPFC subregions in 15 healthy subjects. We evaluated reliability (concordance correlation coefficient [CCC]) across targets, time windows, quantification methods, regions of interest, sensor- vs. source-space, and number of trials. On average, the medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). However, all targets except the most anterior were reliable (CCC > 0.7) using at least one combination of the analytical parameters tested. Longer (20 to 60 ms) and later (30 to 60 ms) windows increased reliability compared to earlier and shorter windows. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials at a medial dlPFC target. Overall, medial dlPFC targeting, wider windows, and peak-to-peak quantification improved reliability. With careful selection of target and analytic parameters, highly reliable EL-TEPs can be extracted from the dlPFC after only a small number of trials.

Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study.

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Acetazolamide as an effective treatment for pilomotor seizures in autoimmune encephalitis.

Pilomotor seizures are strongly associated with autoimmune encephalitis (AE), particularly anti-LGI1 encephalitis. The carbonic anhydrase inhibitor acetazolamide may have special efficacy for treating AE-associated pilomotor seizures. Six patients with AE (five anti-LGI1, one seronegative) and temporal lobe pilomotor seizures (five with seizures inducible by hyperventilation) were treated with acetazolamide, administered in a cycling (2-days-ON, 4-days-OFF) regimen to offset tolerance. Seizures were assessed during epilepsy monitoring unit (EMU) recordings in four inpatients (one of whom also maintained an outpatient seizure diary chronicling 1203 seizures over 1079 days); two outpatients self-reported seizure frequencies. The extended diary revealed an inverse correlation between acetazolamide and proportion of seizures/day: 6%, 2% (days 1, 2 ON); 3%, 13%, 31%, 45% (days 1, 2, 3, 4 OFF). This patient later developed focal status epilepticus upon wean of antiseizure medications during a seropositive AE relapse that was remarkably aborted with acetazolamide monotherapy. The other three EMU patients averaged .56 seizures/day ON, and 3.81 seizures/day OFF (p = .004). The two outpatients reported seizure reductions from 3-5/day to 2/week, and 15-20/day to none, respectively, after initiation of cycling acetazolamide. Likely related to cerebral CO2/pH sensitivity, acetazolamide can be unusually effective in controlling pilomotor seizures in AE, chronically or in acute settings.

Evening prolonged relatively low melanopic equivalent daylight illuminance light exposure increases arousal before and during sleep without altering sleep structure.

Light can influence many psychophysiological functions beyond vision, including alertness, circadian rhythm, and sleep, namely the non-image forming (NIF) effects of light. Melanopic equivalent daylight illuminance (mel-EDI) is currently recommended as the predictor of the NIF effects of light. Although light dose is also critical for entraining and regulating circadian cycle, it is still unknown whether relatively low mel-EDI light exposure for prolonged duration in the evening would affect pre-sleep arousal and subsequent sleep. In all, 18 healthy college students (10 females, mean [standard deviation] age 21.67 [2.03] years) underwent 2 experimental nights with a 1 week interval in a simulated bedroom environment. During experimental nights, participants were either exposed to high or low mel-EDI light (73 versus 38 lx mel-EDI, 90 versus 87 photopic lx at eye level, 150 photopic lx at table level) for 3.5 h before regular bedtime, and their sleep was monitored by polysomnography. Subjective sleepiness, mood, and resting-state electroencephalography during light exposure were also investigated. Results showed no significant differences in sleep structure and sleep quality between the two light conditions, whereas 3.5 h of exposure to high versus low mel-EDI light induced marginally higher physiological arousal in terms of a lower delta but higher beta power density before sleep, as well as a lower delta power density during sleep. Moreover, participants felt happier before sleep under exposure to high versus low mel-EDI light. These findings together with the current literature suggest that evening prolonged relatively low mel-EDI light exposure may mildly increase arousal before and during sleep but affected sleep structure less.

Naturalistic use of psychedelics does not modulate processing of self-related stimuli (but it might modulate attentional mechanisms): An event-related potentials study.

Classic psychedelics are able to profoundly alter the state of consciousness and lead to acute experiences of ego dissolution - the blurring of the distinction between representations of self and the external world. However, whether repeated use of psychedelics is associated with more prolonged and permanent modifications to the concept of self remains to be investigated. Therefore, we conducted a preregistered, cross-sectional study in which experienced psychedelics users (15 or more lifetime experiences with psychedelics; N = 56) were compared to nonusers (N = 57) in terms of neural reactivity to a Self-name (i.e., each participant's own name) stimulus, which is known to robustly activate a representation of self. Two control stimuli were additionally used: an Other-name stimulus, as a passive control condition in which no reaction was required, and a Target-name stimulus, to which participants provided a manual response and which thus constituted an active control condition. Analysis of the amplitude of the P300 ERP component evoked by the Self- or Target-names revealed no difference between the psychedelics users and nonusers. However, psychedelic users exhibited increased P300 amplitude during perception of Other-names. In addition, in comparison to nonusers, psychedelics users exhibited a smaller increase in P300 amplitude when processing the task-relevant Target-names (in relation to both Self- and Other-names). Therefore, our data suggests that regular naturalistic use of psychedelics may not be related to long-term changes in the representation of self, but it might potentially affect the allocation of attentional resources to task-relevant stimuli.

Frequency Analysis of EEG Microstate Sequences in Wakefulness and NREM Sleep.

The majority of EEG microstate analyses concern wakefulness, and the existing sleep studies have focused on changes in spatial microstate properties and on microstate transitions between adjacent time points, the shortest available time scale. We present a more extensive time series analysis of unsmoothed EEG microstate sequences in wakefulness and non-REM sleep stages across many time scales. Very short time scales are assessed with Markov tests, intermediate time scales by the entropy rate and long time scales by a spectral analysis which identifies characteristic microstate frequencies. During the descent from wakefulness to sleep stage N3, we find that the increasing mean microstate duration is a gradual phenomenon explained by a continuous slowing of microstate dynamics as described by the relaxation time of the transition probability matrix. The finite entropy rate, which considers longer microstate histories, shows that microstate sequences become more predictable (less random) with decreasing vigilance level. Accordingly, the Markov property is absent in wakefulness but in sleep stage N3, 10/19 subjects have microstate sequences compatible with a second-order Markov process. A spectral microstate analysis is performed by comparing the time-lagged mutual information coefficients of microstate sequences with the autocorrelation function of the underlying EEG. We find periodic microstate behavior in all vigilance states, linked to alpha frequencies in wakefulness, theta activity in N1, sleep spindle frequencies in N2, and in the delta frequency band in N3. In summary, we show that EEG microstates are a dynamic phenomenon with oscillatory properties that slow down in sleep and are coupled to specific EEG frequencies across several sleep stages.

The impact of social distance on the processing of social evaluation: evidence from brain potentials and neural oscillations.

Previous research indicates that social distance can influence people's social evaluations of others. Individuals tend to evaluate intimate others more positively than distant others. The present study investigates the modulating effect of social distance on the time course underlying individuals' evaluation processes of others using adequate electroencephalography methods. The results reveal that in the initial processing stage, the P2 component is larger when friends are negatively evaluated, whereas this pattern is the opposite for strangers. In the second stage, medial frontal negativity and early mid-frontal theta band activity is enhanced for negative evaluations of friends, whereas this effect is absent in social evaluations of strangers. At the late stage, the P3 is larger for positive evaluations of friends but insensitive to social evaluations of strangers, and the late mid-frontal theta is also modulated by social distance. These findings provide direct and powerful evidence that social distance modulates individuals' evaluations of others with different levels of intimacy throughout all processing stages.

Neural oscillations reflect the individual differences in the temporal perception of audiovisual speech.

Multisensory integration occurs within a limited time interval between multimodal stimuli. Multisensory temporal perception varies widely among individuals and involves perceptual synchrony and temporal sensitivity processes. Previous studies explored the neural mechanisms of individual differences for beep-flash stimuli, whereas there was no study for speech. In this study, 28 subjects (16 male) performed an audiovisual speech/ba/simultaneity judgment task while recording their electroencephalography. We examined the relationship between prestimulus neural oscillations (i.e. the pre-pronunciation movement-related oscillations) and temporal perception. The perceptual synchrony was quantified using the Point of Subjective Simultaneity and temporal sensitivity using the Temporal Binding Window. Our results revealed dissociated neural mechanisms for individual differences in Temporal Binding Window and Point of Subjective Simultaneity. The frontocentral delta power, reflecting top-down attention control, is positively related to the magnitude of individual auditory leading Temporal Binding Windows (auditory Temporal Binding Windows; LTBWs), whereas the parieto-occipital theta power, indexing bottom-up visual temporal attention specific to speech, is negatively associated with the magnitude of individual visual leading Temporal Binding Windows (visual Temporal Binding Windows; RTBWs). In addition, increased left frontal and bilateral temporoparietal occipital alpha power, reflecting general attentional states, is associated with increased Points of Subjective Simultaneity. Strengthening attention abilities might improve the audiovisual temporal perception of speech and further impact speech integration.

Duplex perception reveals brainstem auditory representations are modulated by listeners' ongoing percept for speech.

So-called duplex speech stimuli with perceptually ambiguous spectral cues to one ear and isolated low- versus high-frequency third formant "chirp" to the opposite ear yield a coherent percept supporting their phonetic categorization. Critically, such dichotic sounds are only perceived categorically upon binaural integration. Here, we used frequency-following responses (FFRs), scalp-recorded potentials reflecting phase-locked subcortical activity, to investigate brainstem responses to fused speech percepts and to determine whether FFRs reflect binaurally integrated category-level representations. We recorded FFRs to diotic and dichotic stop-consonants (/da/, /ga/) that either did or did not require binaural fusion to properly label along with perceptually ambiguous sounds without clear phonetic identity. Behaviorally, listeners showed clear categorization of dichotic speech tokens confirming they were heard with a fused, phonetic percept. Neurally, we found FFRs were stronger for categorically perceived speech relative to category-ambiguous tokens but also differentiated phonetic categories for both diotically and dichotically presented speech sounds. Correlations between neural and behavioral data further showed FFR latency predicted the degree to which listeners labeled tokens as "da" versus "ga." The presence of binaurally integrated, category-level information in FFRs suggests human brainstem processing reflects a surprisingly abstract level of the speech code typically circumscribed to much later cortical processing.

Mismatch negativity as a marker of auditory pattern separation.

To what extent does incidental encoding of auditory stimuli influence subsequent episodic memory for the same stimuli? We examined whether the mismatch negativity (MMN), an event-related potential generated by auditory change detection, is correlated with participants' ability to discriminate those stimuli (i.e. targets) from highly similar lures and from dissimilar foils. We measured the MMN in 30 young adults (18-32 years, 18 females) using a passive auditory oddball task with standard and deviant 5-tone sequences differing in pitch contour. After exposure, all participants completed an incidental memory test for old targets, lures, and foils. As expected, participants at test exhibited high sensitivity in recognizing target items relative to foils and lower sensitivity in recognizing target items relative to lures. Notably, we found a significant correlation between MMN amplitude and lure discrimination, but not foil discrimination. Our investigation shows that our capacity to discriminate sensory inputs at encoding, as measured by the MMN, translates into precision in memory for those inputs.

Inter-individual variability during neurodevelopment: an investigation of linear and nonlinear resting-state EEG features in an age-homogenous group of infants.

Electroencephalography measures are of interest in developmental neuroscience as potentially reliable clinical markers of brain function. Features extracted from electroencephalography are most often averaged across individuals in a population with a particular condition and compared statistically to the mean of a typically developing group, or a group with a different condition, to define whether a feature is representative of the populations as a whole. However, there can be large variability within a population, and electroencephalography features often change dramatically with age, making comparisons difficult. Combined with often low numbers of trials and low signal-to-noise ratios in pediatric populations, establishing biomarkers can be difficult in practice. One approach is to identify electroencephalography features that are less variable between individuals and are relatively stable in a healthy population during development. To identify such features in resting-state electroencephalography, which can be readily measured in many populations, we introduce an innovative application of statistical measures of variance for the analysis of resting-state electroencephalography data. Using these statistical measures, we quantified electroencephalography features commonly used to measure brain development-including power, connectivity, phase-amplitude coupling, entropy, and fractal dimension-according to their intersubject variability. Results from 51 6-month-old infants revealed that the complexity measures, including fractal dimension and entropy, followed by connectivity were the least variable features across participants. This stability was found to be greatest in the right parietotemporal region for both complexity feature, but no significant region of interest was found for connectivity feature. This study deepens our understanding of physiological patterns of electroencephalography data in developing brains, provides an example of how statistical measures can be used to analyze variability in resting-state electroencephalography in a homogeneous group of healthy infants, contributes to the establishment of robust electroencephalography biomarkers of neurodevelopment through the application of variance analyses, and reveals that nonlinear measures may be most relevant biomarkers of neurodevelopment.

Multimodal-based machine learning approach to classify features of internet gaming disorder and alcohol use disorder: A sensor-level and source-level resting-state electroencephalography activity and neuropsychological study.

OBJECTIVES: Addictions have recently been classified as substance use disorder (SUD) and behavioral addiction (BA), but the concept of BA is still debatable. Therefore, it is necessary to conduct further neuroscientific research to understand the mechanisms of BA to the same extent as SUD. The present study used machine learning (ML) algorithms to investigate the neuropsychological and neurophysiological aspects of addictions in individuals with internet gaming disorder (IGD) and alcohol use disorder (AUD). METHODS: We developed three models for distinguishing individuals with IGD from those with AUD, individuals with IGD from healthy controls (HCs), and individuals with AUD from HCs using ML algorithms, including L1-norm support vector machine, random forest, and L1-norm logistic regression (LR). Three distinct feature sets were used for model training: a unimodal-electroencephalography (EEG) feature set combined with sensor- and source-level feature; a unimodal-neuropsychological feature (NF) set included sex, age, depression, anxiety, impulsivity, and general cognitive function, and a multimodal (EEG + NF) feature set. RESULTS: The LR model with the multimodal feature set used for the classification of IGD and AUD outperformed the other models (accuracy: 0.712). The important features selected by the model highlighted that the IGD group had differential delta and beta source connectivity between right intrahemispheric regions and distinct sensor-level EEG activities. Among the NFs, sex and age were the important features for good model performance. CONCLUSIONS: Using ML techniques, we demonstrated the neurophysiological and neuropsychological similarities and differences between IGD (a BA) and AUD (a SUD).

The effects of different acetylcholinesterase inhibitors on EEG patterns in patients with Alzheimer's disease: A systematic review.

OBJECTIVE: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia. The early diagnosis of AD is an important factor for the control of AD progression. Electroencephalography (EEG) can be used for early diagnosis of AD. Acetylcholinesterase inhibitors (AChEIs) are also used for the amelioration of AD symptoms. In this systematic review, we reviewed the effect of different AChEIs including donepezil, rivastigmine, tacrine, physostigmine, and galantamine on EEG patterns in patients with AD. METHODS: PubMed electronic database was searched and 122 articles were found. After removal of unrelated articles, 24 articles were selected for the present study. RESULTS: AChEIs can decrease beta, theta, and delta frequency bands in patients with AD. However, conflicting results were found for alpha band. Some studies have shown increased alpha frequency, while others have shown decreased alpha frequency following treatment with AChEIs. The only difference was the type of drug. CONCLUSIONS: We found that studies reporting the decreased alpha frequency used donepezil and galantamine, while studies reporting the increased alpha frequency used rivastigmine and tacrine. It was suggested that future studies should focus on the effect of different AChEIs on EEG bands, especially alpha frequency in patients with AD, to compare their effects and find the reason for their different influence on EEG patterns. Also, differences between the effects of AChEIs on oligodendrocyte differentiation and myelination may be another important factor. This is the first article investigating the effect of different AChEIs on EEG patterns in patients with AD.