Theta Band Activity Research Articles

Do smaller P300 amplitudes in schizophrenia result from larger variability in temporal processing?

The P3b is a prominent event-related potential (ERP) with maximal amplitude between 250 ms and 500 ms after the onset of a rare target stimulus within a sequence of standard non-target stimuli (oddball paradigm). Several studies found reduced P3b amplitudes in patients with schizophrenia compared to neurotypicals. Our work and the literature suggest that temporal imprecision may play a large pathophysiological role in schizophrenia. Here, we investigated whether reduced P3b amplitudes result from reduced neural activity (power) or temporal imprecision (inter-trial phase coherence; ITC) in delta and theta bands, using two EEG datasets from different studies with different oddball paradigms (Study 1: 19 patients with schizophrenia and 17 matched controls, Study 2: 26 patients and 26 controls). Both studies revealed typical P3b ERP components with smaller amplitudes in patients. Reduced ITC in patients was found in the delta band, which correlated with P3b peak amplitudes for all participant groups (ρ = 0.58–0.89). In Study 1, we also found significant differences between patients and controls in ITC in the theta band, which also correlated with P3b peak amplitudes (patients’ ρ = 0.64, controls’ ρ = 0.54). This was not found in Study 2. The results indicate that P3b amplitude reduction in patients with schizophrenia is linked to a reduction in temporal precision of neural activity. These results expand the notion of imprecision in temporal processing at phenomenological, psychological, and neurological levels that have been related to disturbances of the sense of self. They confirm that temporal imprecision may be more important than the reduction of neural activity itself.

Spectral EEG and heart rate changes associated with leg movements during the suggested immobilization test in patients with restless legs syndrome.

Restless legs syndrome is usually associated with periodic limb movements during sleep, which are defined as repetitive, stereotyped movements in sleep. Changes in spectral analysis of electroencephalography and heart rate were shown to be associated with periodic limb movements during sleep and non-periodic leg movements in sleep. Considering the circadian distribution of symptoms of restless legs syndrome, we investigated spectral electroencephalography and heart rate accompanying periodic limb movements, isolated leg movements and short-interval leg movements during suggested immobilization test. The mean age of 53 patients was 51.9 ± 13 years, 54.7% were females. Prominent increases in electroencephalography activation were associated with periodic limb movements, isolated leg movements and short-interval leg movements during the suggested immobilization test, which were significant in all spectral bands (p < 0.001). An increase in all electroencephalography bands started ~10 s before periodic limb movements, isolated leg movements and short-interval leg movements; increases in delta and theta band activities ended ~10 s after the movements, while increases in alpha and beta band activities lasted for about ~20 s. Maximum increases in delta, theta, alpha and beta bands were all observed after periodic limb movements and short-interval leg movements, but before isolated leg movements in theta and alpha bands, and after isolated leg movements in delta and beta bands. A notably longer increase in alpha and beta bands was evident for periodic limb movements and short-interval leg movements. An increase in heart rate was prominent at 4-12 s after movement onset in short-interval leg movements, being significantly higher than those associated with periodic limb movements and isolated leg movements. Our study shows that, in patients with restless legs syndrome, periodic limb movements, isolated leg movements and short-interval leg movements during suggested immobilization test are associated with prominent cortical and cardiac activation, which warrants confirmation in larger restless legs syndrome cohorts and requires long-term follow-up studies to delineate its possible clinical consequences.

Neurophysiological dynamics of metacontrol states: EEG insights into conflict regulation

Understanding the neural mechanisms underlying metacontrol and conflict regulation is crucial for insights into cognitive flexibility and persistence. This study employed electroencephalography (EEG), EEG-beamforming and directed connectivity analyses to explore how varying metacontrol states influence conflict regulation at a neurophysiological level. Metacontrol states were manipulated by altering the frequency of congruent and incongruent trials across experimental blocks in a modified flanker task, and both behavioral and electrophysiological measures were analyzed. Behavioral data confirmed the experimental manipulation's efficacy, showing an increase in persistence bias and a reduction in flexibility bias during increased conflict regulation. Electrophysiologically, theta band activity paralleled the behavioral data, suggesting that theta oscillations reflect the mismatch between expected metacontrol bias and actual task demands. Alpha and beta band dynamics differed across experimental blocks, though these changes did not directly mirror behavioral effects. Post-response alpha and beta activity were more pronounced in persistence-biased states, indicating a neural reset mechanism preparing for future cognitive demands. By using a novel artificial neural networks method, directed connectivity analyses revealed enhanced inter-regional communication during persistence states, suggesting stronger top-down control and sensorimotor integration. Overall, theta band activity was closely tied to metacontrol processes, while alpha and beta bands played a role in resetting the neural system for upcoming tasks. These findings provide a deeper understanding of the neural substrates involved in metacontrol and conflict monitoring, emphasizing the distinct roles of different frequency bands in these cognitive processes.

Neurophysiological principles underlying predictive coding during dynamic perception-action integration

A major concept in cognitive neuroscience is that brains are “prediction machines”. Yet, conceptual frameworks on how perception and action become integrated still lack the concept of predictability and it is unclear how neural processes may implement predictive coding during dynamic perception-action integration. We show that distinct neurophysiological mechanisms of nonlinearly directed connectivities in the theta and alpha band between cortical structures underlie these processes. During the integration of perception and motor codes, especially theta band activity in the insular cortex and temporo-hippocampal structures is modulated by the predictability of upcoming information. Here, the insular cortex seems to guide processes. Conversely, the retrieval of such integrated perception-action codes during actions heavily relies on alpha band activity. Here, directed top-down influence of alpha band activity from inferior frontal structures on insular and temporo-hippocampal structures is key. This suggests that these top-down effects reflect attentional shielding of retrieval processes operating in the same neuroanatomical structures previously involved in the integration of perceptual and motor codes. Through neurophysiology, the present study connects predictive coding mechanisms with frameworks specifying the dynamic integration of perception and action.

Decoding Depth of Meditation: Electroencephalography Insights From Expert Vipassana Practitioners

BackgroundMeditation practices have demonstrated numerous psychological and physiological benefits, but capturing the neural correlates of varying meditative depths remains challenging. In this study, we aimed to decode self-reported time-varying meditative depth in expert practitioners using electroencephalography (EEG). MethodsExpert Vipassana meditators (n = 34) participated in 2 separate sessions. Participants reported their meditative depth on a personally defined 1 to 5 scale using both traditional probing and a novel spontaneous emergence method. EEG activity and effective connectivity in theta, alpha, and gamma bands were used to predict meditative depth using machine/deep learning, including a novel method that fused source activity and connectivity information. ResultsWe achieved significant accuracy in decoding self-reported meditative depth across unseen sessions. The spontaneous emergence method yielded improved decoding performance compared with traditional probing and correlated more strongly with postsession outcome measures. Best performance was achieved by a novel machine learning method that fused spatial, spectral, and connectivity information. Conventional EEG channel-level methods and preselected default mode network regions fell short in capturing the complex neural dynamics associated with varying meditation depths. ConclusionsThis study demonstrates the feasibility of decoding personally defined meditative depth using EEG. The findings highlight the complex, multivariate nature of neural activity during meditation and introduce spontaneous emergence as an ecologically valid and less obtrusive experiential sampling method. These results have implications for advancing neurofeedback techniques and enhancing our understanding of meditative practices.

Render help or stand by? The effect of group size on third-party punishment and its neural mechanisms

Third-party punishment (TPP) is the punishment that an individual executes on a violator as a third party or observer to maintain social norms. Many studies have provided insights into the neural mechanisms of third-party punishment in group environments. Still, only some studies have focused on the neural mechanisms of third-party punishment in different group sizes. This study used EEG analysis to explore the effects of group size on third-party punishment and its neural activity characteristics from the context of gain and loss. The results show that the punishment rate and amount of the third party in the small group size and loss context were significantly higher than that in the large group size and gain context. EEG results showed that third-party punishment in small groups induced greater P2 than in large groups. In the loss context, the third-party punishment in the large group size induced more negative LNP and activated more theta band activation than in the small group. The results showed that the motivation of the third party to seek a positive reputation in the small size exceeds the balance of its economic interests and tends to punish the violator for maintaining fair norms. The loss context plays a promoting role in this process. However, in the large size, the third-party consideration of its interests was stronger than the willingness to maintain social norms. This study provided neuroscientific evidence for third-party punishment to maintain fair norms in a group environment and further explanations from neuroscience for understanding Indirect Reciprocity Theory.

Rapid reconfiguration of cortical networks after repeated exposure to visual-vestibular conflicts

Visual-vestibular conflicts can induce motion sickness and further postural instability. Visual-vestibular habituation is recommended to reduce the symptoms of motion sickness and improve postural stability with an altered multisensory reweighting progress. However, it is unclear how the human brain reweights multisensory information after repeated exposure to visual-vestibular conflicts. Therefore, we synchronized a rotating platform and a virtual scene to present visual-vestibular congruent (natural visual stimulation) and incongruent (conflicted visual stimulation) conditions and collected EEG and center of pressure (COP) data. We constructed the effective brain connectivity of region of interest (ROI) derived from source-space EEG in theta-band activity, and quantified the postural stability and the inflow and outflow of each ROI. We found repeated exposure to congruent and incongruent conditions both decreased COP path length and increased COP complexity. Besides, we found that repeated exposure to the incongruent environment decreased the inflow into visual cortex, suggesting the brain down-weighted the less reliable visual information for postural stability. In contrast, repeated exposure to the congruent environment increased the inflow into posterior parietal cortex and the outflow from visual cortex and S1, suggesting an increase in efficiency of multisensory integration. We concluded that repeated exposure to congruent and incongruent conditions both improved postural stability with different multisensory reweighting patterns as revealed by different dynamic changes of brain networks.

Mindfulness-based Neurofeedback: A Systematic Review of EEG and fMRI studies.

Neurofeedback concurrent with mindfulness meditation may reveal meditation effects on the brain and facilitate improved mental health outcomes. Here, we systematically reviewed EEG and fMRI studies of mindfulness meditation with neurofeedback (mbNF) and followed PRISMA guidelines. We identified 10 fMRI reports, consisting of 177 unique participants, and 9 EEG reports, consisting of 242 participants. Studies of fMRI focused primarily on downregulating the default-mode network (DMN). Although studies found decreases in DMN activations during neurofeedback, there is a lack of evidence for transfer effects, and the majority of studies did not employ adequate controls, e.g. sham neurofeedback. Accordingly, DMN decreases may have been confounded by general task-related deactivation. EEG studies typically examined alpha, gamma, and theta frequency bands, with the most robust evidence supporting the modulation of theta band activity. Both EEG and fMRI mbNF have been implemented with high fidelity in clinical populations. However, the mental health benefits of mbNF have not been established. In general, mbNF studies would benefit from sham-controlled RCTs, as well as clear reporting (e.g. CRED-NF).

Electroencephalography-based endogenous phenotype of diagnostic transition from major depressive disorder to bipolar disorder

The neuropathology of mood disorders, including the diagnostic transition from major depressive disorder (MDD) to bipolar disorder (BD), is poorly understood. This study investigated resting-state electroencephalography (EEG) activity in patients with MDD and those whose diagnosis changed from MDD to BD. Among sixty-eight enrolled patients with MDD, the diagnosis of 17 patients converted to BD during the study period. We applied machine learning techniques to differentiate the two groups using sensor- and source-level EEG features. At the sensor level, patients with BD showed higher theta band power at the AF3 channel and low-alpha band power at the FC5 channel compared to patients with MDD. At the source level, patients with BD showed higher theta band activity in the right anterior cingulate and low-alpha band activity in the left parahippocampal gyrus. These four EEG features were selected for discriminating between BD and MDD with the best classification performance showing an accuracy of 80.88%, a sensitivity of 76.47%, and a specificity of 82.35%. Our findings revealed distinct theta and low-alpha band activities in patients with BD and MDD. These differences could potentially serve as candidate neuromarkers for the diagnosis and diagnostic transition between the two distinct mood disorders.

Transient Increases in Neural Oscillations and Motor Deficits in a Mouse Model of Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms like tremors and bradykinesia. PD's pathology involves the aggregation of α-synuclein and loss of dopaminergic neurons, leading to altered neural oscillations in the cortico-basal ganglia-thalamic network. Despite extensive research, the relationship between the motor symptoms of PD and transient changes in brain oscillations before and after motor tasks in different brain regions remain unclear. This study aimed to investigate neural oscillations in both healthy and PD model mice using local field potential (LFP) recordings from multiple brain regions during rest and locomotion. The histological evaluation confirmed the significant dopaminergic neuron loss in the injection side in 6-OHDA lesioned mice. Behavioral tests showed motor deficits in these mice, including impaired coordination and increased forelimb asymmetry. The LFP analysis revealed increased delta, theta, alpha, beta, and gamma band activity in 6-OHDA lesioned mice during movement, with significant increases in multiple brain regions, including the primary motor cortex (M1), caudate-putamen (CPu), subthalamic nucleus (STN), substantia nigra pars compacta (SNc), and pedunculopontine nucleus (PPN). Taken together, these results show that the motor symptoms of PD are accompanied by significant transient increases in brain oscillations, especially in the gamma band. This study provides potential biomarkers for early diagnosis and therapeutic evaluation by elucidating the relationship between specific neural oscillations and motor deficits in PD.

Vagus nerve electroneurogram-based detection of acute kainic acid induced seizures.

Seizures produce autonomic symptoms, mainly sympathetic but also parasympathetic in origin. Within this context, the vagus nerve is a key player as it carries information from the different organs to the brain and vice versa. Hence, exploiting vagal neural traffic for seizure detection might be a promising tool to improve the efficacy of closed-loop Vagus Nerve Stimulation. This study developed a VENG detection algorithm that effectively detects seizures by emphasizing the loss of spontaneous rhythmicity associated with respiration in acute intrahippocampal Kainic Acid rat model. Among 20 induced seizures in six anesthetized rats, 13 were detected (sensitivity: 65%, accuracy: 92.86%), with a mean VENG-detection delay of 25.3 ± 13.5 s after EEG-based seizure onset. Despite variations in detection parameters, 7 out of 20 seizures exhibited no ictal VENG modifications and remained undetected. Statistical analysis highlighted a significant difference in Delta, Theta and Beta band evolution between detected and undetected seizures, in addition to variations in the magnitude of HR changes. Binomial logistic regression analysis confirmed that an increase in delta and theta band activity was associated with a decreased likelihood of seizure detection. This results suggest the possibility of distinct seizure spreading patterns between the two groups which may results in differential activation of the autonomic central network. Despite notable progress, limitations, particularly the absence of respiration recording, underscore areas for future exploration and refinement in closed-loop stimulation strategies for epilepsy management. This study constitutes the initial phase of a longitudinal investigation, which will subsequently involve reproducing these experiments in awake conditions with spontaneous recurrent seizures.

EEG signature of near-death-like experiences during syncope-induced periods of unresponsiveness

During fainting, disconnected consciousness may emerge in the form of dream-like experiences. Characterized by extra-ordinary and mystical features, these subjective experiences have been associated to near-death-like experiences (NDEs-like). We here aim to assess brain activity during syncope-induced disconnected consciousness by means of high-density EEG monitoring. Transient loss of consciousness and unresponsiveness were induced in 27 healthy volunteers through hyperventilation, orthostasis, and Valsalva maneuvers. Upon awakening, subjects were asked to report memories, if any. The Greyson NDE scale was used to evaluate the potential phenomenological content experienced during the syncope-induced periods of unresponsiveness. EEG source reconstruction assessed cortical activations during fainting, which were regressed out with subjective reports collected upon recovery of normal consciousness. We also conducted functional connectivity, graph-theoretic and complexity analyses. High quality high-density EEG data were obtained in 22 volunteers during syncope and unresponsiveness (lasting 22±8 s). NDE-like features (Greyson NDE scale total score ≥7/32) were apparent for eight volunteers and characterized by higher activity in delta, theta and beta2 bands in temporal and frontal regions. The richness of the NDE-like content was associated with delta, theta and beta2 bands cortical current densities, in temporal, parietal and frontal lobes, including insula, right temporoparietal junction, and cingulate cortex. Our analyses also revealed a higher complexity and that networks related to delta, theta, and beta2 bands were characterized by a higher overall connectivity paralleled by a higher segregation (i.e., local efficiency) and a higher integration (i.e., global efficiency) for the NDE-like group compared to the non-NDE-like group. Fainting-induced NDE-like episodes seem to be sustained by surges of neural activity representing promising markers of disconnected consciousness.

Altered oscillatory neural dynamics related to word prediction in older adult readers

ABSTRACT The engagement of predictive mechanisms during language comprehension can facilitate processing and modulate neural oscillatory activity. These modulations include alpha-band activity decreases prior to expected words, reflecting anticipatory preparation, and frontal theta-band activity following unexpected words, reflecting engagement of cognitive control. It remains unknown how these oscillatory dynamics are impacted by aging. Here, we re-analysed previously collected EEG data from a sentence reading experiment with older adult participants to examine oscillatory responses to expected and unexpected words. Compared to younger adults, older adults’ frontal theta responses following unexpected words were delayed and reduced in magnitude. Alpha-band decreases prior to expected words were comparable across age groups, but only young adults’ pre-stimulus alpha activity was correlated with the post-stimulus frontal theta response. These results suggest older adults may engage anticipatory neural mechanisms comparably to younger adults, but do not engage the same control mechanisms following prediction errors.

The human brain deals with violating general color or depth knowledge in different time courses

Utilizing the high temporal resolution of event-related potentials (ERPs), we compared the time course of processing incongruent color versus 3D-depth information. Participants were asked to judge whether the food color (color condition) or 3D structure (3D-depth condition) was congruent or incongruent with their previous knowledge and experience. The behavioral results showed that the reaction times in the congruent 3D-depth condition were slower than those in the congruent color condition. The reaction times in the incongruent 3D-depth condition were slower than those in the incongruent color condition. The ERP results showed that incongruent color stimuli induced a larger N270, larger P300, and smaller N400 components in the fronto-central region than the congruent color stimuli. Incongruent 3D-depth stimuli induced a smaller N1 in the occipital region, larger P300 and smaller N400 in the parietal-occipital region than congruent 3D-depth stimuli. The time–frequency analysis found that incongruent color stimuli induced a larger theta band (360–580 ms) activation in the fronto-central region than congruent color stimuli. Incongruent 3D-depth stimuli induced larger alpha and beta bands (240–350 ms) activation in the parietal region than congruent 3D-depth stimuli. Our results suggest that the human brain deals with violating general color or depth knowledge in different time courses. We speculate that the depth perception conflict was dominated by solving the problem with visual processing, whereas the color perception conflict was dominated by solving the problem with semantic violation.

Event segmentation in ADHD: neglect of social information and deviant theta activity point to a mechanism underlying ADHD

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is one of the most frequently diagnosed psychiatric conditions in children and adolescents. Although the symptoms appear to be well described, no coherent conceptual mechanistic framework integrates...

Interictal EEG features as computational biomarkers of West syndrome.

West syndrome (WS) is a devastating epileptic encephalopathy with onset in infancy and early childhood. It is characterized by clustered epileptic spasms, developmental arrest, and interictal hypsarrhythmia on electroencephalogram (EEG). Hypsarrhythmia is considered the hallmark of WS, but its visual assessment is challenging due to its wide variability and lack of a quantifiable definition. This study aims to analyze the EEG patterns in WS and identify computational diagnostic biomarkers of the disease. Linear and non-linear features derived from EEG recordings of 31 WS patients and 20 age-matched controls were compared. Subsequently, the correlation of the identified features with structural and genetic abnormalities was investigated. WS patients showed significantly elevated alpha-band activity (0.2516 vs. 0.1914, p < 0.001) and decreased delta-band activity (0.5117 vs. 0.5479, p < 0.001), particularly in the occipital region, as well as globally strengthened theta-band activity (0.2145 vs. 0.1655, p < 0.001) in power spectrum analysis. Moreover, wavelet-bicoherence analysis revealed significantly attenuated cross-frequency coupling in WS patients. Additionally, bi-channel coherence analysis indicated minor connectivity alterations in WS patients. Among the four non-linear characteristics of the EEG data (i.e., approximate entropy, sample entropy, permutation entropy, and wavelet entropy), permutation entropy showed the most prominent global reduction in the EEG of WS patients compared to controls (1.4411 vs. 1.5544, p < 0.001). Multivariate regression results suggested that genetic etiologies could influence the EEG profiles of WS, whereas structural factors could not. A combined global strengthening of theta activity and global reduction of permutation entropy can serve as computational EEG biomarkers for WS. Implementing these biomarkers in clinical practice may expedite diagnosis and treatment in WS, thereby improving long-term outcomes.

Modulation of EEG Signals by Visual and Auditory Distractors in Virtual Reality-based Continuous Performance Tests.

Compared to traditional continuous performance tasks, virtual reality-based continuous performance tests (VR-CPT) offer higher ecological validity.While previous studies have primarily focused on behavioral outcomes in VR-CPT and incorporated various distractors to enhance ecological realism, little attention has been paid to the effects of distractors on EEG. Therefore, our study aimed to investigate the influence of distractors on EEG during VR-CPT. We studied visual distractors and auditory distractors separately, recruiting 68 subjects (M=20.82, SD=1.72) and asking each to complete four tasks. These tasks were categorized into four groups according to the presence or absence of visual and auditory distractors. We conducted paired t-tests on the mean relative power of the five electrodes in the ROI region across different frequency bands. Significant differences were found in theta waves between Group 3 (M = 2.49, SD = 2.02) and Group 4 (M = 2.68, SD = 2.39) (p < 0.05); in alpha waves between Group 3 (M = 2.08, SD = 3.73) and Group 4 (M = 3.03, SD = 4.60) (p < 0.001); and in beta waves between Group 1 (M = -4.44, SD = 2.29) and Group 2 (M = -5.03, SD = 2.48) (p < 0.001), as well as between Group 3 (M = -4.48, SD = 2.03) and Group 4 (M = -4.67, SD = 2.23) (p < 0.05). The incorporation of distractors in VR-CPT modulates EEG signals across different frequency bands, with visual distractors attenuating theta band activity, auditory distractors enhancing alpha band activity, and both types of distractors reducing beta oscillations following target stimuli. This insight holds significant promise for the rehabilitation of children and adolescents with attention deficits.

Neural oscillations guiding action during effects imagery

Goal-directed acting requires the integration of sensory information but can also be performed without direct sensory input. Examples of this can be found in sports and can be conceptualized by feedforward processes. There is, however, still a lack of understanding of the temporal neural dynamics and neuroanatomical structures involved in such processes. In the current study, we used EEG beamforming methods and examined 37 healthy participants in two well-controlled experiments varying the necessity of anticipatory processes during goal-directed action. We found that alpha and beta activity in the medial and posterior cingulate cortex enabled feedforward predictions about the position of an object based on the latest sensorimotor state. On this basis, theta band activity seems more related to sensorimotor representations, while beta band activity would be more involved in setting up the structure of the neural representations themselves. Alpha band activity in sensory cortices reflects an intensified gating of the anticipated perceptual consequences of the to-be-executed action. Together, the findings indicate that goal-directed acting through the anticipation of the predicted state of an effector is based on accompanying processes in multiple frequency bands in midcingulate and sensory brain regions.

Effects of Catecholaminergic and Transcranial Direct Current Stimulation on Response Inhibition.

The principle of gain control determines the efficiency of neuronal processing and can be enhanced with pharmacological or brain stimulation methods. It is a key factor for cognitive control, but the degree of how much gain control may be enhanced underlies a physical limit. To investigate whether methylphenidate (MPH) and transcranial direct current stimulation (tDCS) share common underlying mechanisms and cognitive effects, we administered MPH and anodal tDCS (atDCS) over the right inferior frontal gyrus both separately and combined, while healthy adult participants (n = 104) performed a response selection and inhibition task. The recorded EEG data were analyzed with a focus on theta band activity, and source estimation analyses were conducted. The behavioral data show that MPH and atDCS revealed interactive effects on the ability to inhibit responses. Both MPH and atDCS modulated task-related theta oscillations in the supplementary motor area when applied separately, making a common underlying mechanism likely. When both stimulation methods were combined, there was no doubling of effects in the supplementary motor area but a shift to inferior frontal areas in the cortical network responsible for theta-driven processing. The results indicate that both MPH and atDCS likely share a common underlying neuronal mechanism, and interestingly, they demonstrate interactive effects when combined, which are most likely due to the physical limitations of gain control increases. The current study provides critical groundwork for future combined applications of MPH and non-invasive brain stimulation.

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer’s disease

Neuronal dysfunction and cognitive deterioration in Alzheimer’s disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.