Depression and anxiety are common mental disorders that often occur together. Stress is an important risk factor for both disorders, affecting pathophysiological processes through epigenetic changes ...that mediate gene–environment interactions. In this study, we explored two proposed models about the dynamic nature of DNA methylation in anxiety and depression: a stable change, in which DNA methylation accumulates over time as a function of the duration of clinical symptoms of anxiety and depression, or a flexible change, in which DNA methylation correlates with the acute severity of clinical symptoms. Symptom severity was assessed using clinical questionnaires for anxiety and depression (BDI-II, IDS-C, and HAM-A), and the current episode and the total lifetime symptom duration was obtained from patients’ medical records. Peripheral blood DNA methylation levels were determined for the BDNF, COMT, and SLC6A4 genes. We found a significant negative correlation between COMT_1 amplicon methylation and acute symptom scores, with BDI-II (R(22) = 0.190, p = 0.033), IDS-C (R(22) = 0.199, p = 0.029), and HAM-A (R(22) = 0.231, p = 0.018) all showing a similar degree of correlation. Our results suggest that DNA methylation follows flexible dynamics, with methylation levels closely associated with acute clinical presentation rather than with the duration of anxiety and depression. These results provide important insights into the dynamic nature of DNA methylation in anxiety and affective disorders and contribute to our understanding of the complex interplay between stress, epigenetics, and individual phenotype.
Introduction
Patients with schizophrenia typically exhibit deficits in working memory (WM) associated with abnormalities in brain activity. Alterations in the encoding, maintenance and retrieval ...phases of sequential WM tasks are well established. However, due to the heterogeneity of symptoms and complexity of its neurophysiological underpinnings, differential diagnosis remains a challenge. We conducted an electroencephalographic (EEG) study during a visual WM task in fifteen schizophrenia patients and fifteen healthy controls. We hypothesized that EEG abnormalities during the task could be identified, and patients successfully classified by an interpretable machine learning algorithm.
Methods
We tested a custom dense attention network (DAN) machine learning model to discriminate patients from control subjects and compared its performance with simpler and more commonly used machine learning models. Additionally, we analyzed behavioral performance, event-related EEG potentials, and time-frequency representations of the evoked responses to further characterize abnormalities in patients during WM.
Results
The DAN model was significantly accurate in discriminating patients from healthy controls,
ACC
= 0.69, SD = 0.05. There were no significant differences between groups, conditions, or their interaction in behavioral performance or event-related potentials. However, patients showed significantly lower alpha suppression in the task preparation, memory encoding, maintenance, and retrieval phases
F
(1,28) = 5.93,
p
= 0.022, η
2
= 0.149. Further analysis revealed that the two highest peaks in the attention value vector of the DAN model overlapped in time with the preparation and memory retrieval phases, as well as with two of the four significant time-frequency ROIs.
Discussion
These results highlight the potential utility of interpretable machine learning algorithms as an aid in diagnosis of schizophrenia and other psychiatric disorders presenting oscillatory abnormalities.
Despite accumulating evidence of inter and intraindividual variability in response to theta burst stimulation, it is widely believed that in therapeutic applications, repeated sessions can have a ...“build‐up” effect that increases the response over and above that seen in a single session. However, strong evidence for this is lacking. Therefore, we examined whether daily administration of intermittent theta burst stimulation (iTBS) over the primary motor cortex induces cumulative changes in transcranial magnetic stimulation measures of cortical excitability, above the changes induced by sham stimulation. Over five consecutive days, 20 healthy participants received either active iTBS or sham stimulation. Each day, baseline measures of cortical excitability were assessed before and up to 30 min after the intervention. There was no significant difference in the rate of response between iTBS and sham stimulation on any of the 5 days. There was no iTBS specific cumulative increase of corticospinal excitability. The likelihood that an individual would remain a responder from day‐to‐day was low in both groups, implying high within‐subject variability of both active and sham iTBS after‐effects. In contrast, we found a high within‐subject repeatability of resting and active motor threshold, and baseline motor‐evoked potential amplitude. In summary, sham stimulation has similar effect to active iTBS on corticospinal excitability, even when applied repeatedly for 5 days. Our results might be relevant to research and clinical applications of theta burst stimulation protocols.
We examined whether daily administration of iTBS over the primary motor cortex induce cumulative changes in TMS measures of corticospinal excitability above the changes induced by sham stimulation. We found no significant difference between the iTBS and sham groups in any of the five consecutive days of stimulation. There was no iTBS specific cumulative increase of cortical excitability. Our results might be relevant to research and clinical applications of theta burst stimulation protocols.
Abstract
Background
Alzheimer’s disease is characterized by cortical hyperexcitability in the early stages, which may be attributed to the intricate interplay between tau and amyloid β pathologies. ...To combat the propagation of tau pathology and cognitive decline, it may be beneficial to maintain a high degree of functional brain network segregation. Additionally, the use of non‐invasive brain stimulation techniques to alter cortical excitability could help alleviate cognitive deficits. However, it is unclear how these interventions are related to tau or amyloid biomarkers.
Method
In this study, 530 participants aged 40 to 65 from the Barcelona Brain Health Initiative cohort were analyzed to investigate the connection between plasma concentration of tau phosphorylated at amino acid 181 (pTau181), cortical excitability, and segregation of functional brain networks. Participants had functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and pTau181 available. A subset of 47 participants also underwent transcranial magnetic stimulation with concurrent EEG (TMS‐EEG). Cortical excitability was assessed using the one‐over‐f slope of the EEG power spectrum (1/
f
‐slope) and evoked response to a TMS perturbation (TEP) of the left prefrontal cortex (L‐PFC) between 160‐240ms post single‐pulse TMS. The degree of segregation between major functional networks was measured from fMRI data using the system segregation statistic.
Result
A generalized linear model with a gamma distribution (Table 1) revealed that steeper 1/
f
‐slope correlated with higher pTau181 concentration, particularly in participants older than 53 years of age (Figure 1.A), or system segregation below 0.28 (Figure 1.B). A multiple linear regression within the TMS‐EEG subsample (Table 2) revealed that the TEP response correlated positively with pTau181 as age increased, and that this model, despite including a smaller sample size, better explained pTau181 concentrations.
Conclusion
The study shows that cortical excitability is related to pTau181 based on age and system segregation. The TEP response is a more sensitive marker than unperturbed EEG metrics in explaining the relation between excitability and pTau181 concentrations. Combined TMS with EEG could potentially be an inexpensive and scalable approach for early identification and longitudinal tracking of middle‐aged adults at risk for cognitive decline and dementia.
The aim of this paper is to test the thesis from media history that by transforming ways of presenting, transmitting, and receiving, technological innovations also transform individual ...consciousness-ways of apprehending, experiencing, remembering, recollecting, recognizing, and understanding. We attempt to do this with the aid of an empirical, cognitive approach. We are specifically interested in the higher cognitive processes of understanding and recollecting while reading select poetic texts on paper and on screen. We do not take a position on which way of reading is superior. Our interest is in how the complementarity of cognitive processes the two reading media facilitate and cognitive processes the characteristics of select texts generate influence the "quality" of recollection and understanding. Among the most interesting results from the pilot study stage, which employs a kind of behavioral test on young subjects, is that poetry that depends on regular use (repetition) of rhyme or rhyme and meter in order to support understanding and recollecting processes is not better committed to memory than more freely structured (and less regular) poetry. Neither do results show statistically relevant differences between the two ways of reading, leading us to conclude that textual traits rather than presentation mode produce "quality" reading. We close with thoughts about the research project's limitations and describe its continuation.
Schizophrenia exerts its devastating effects mostly by causing a profound and poorly understood inability to function, affecting different aspects of everyday life from daily activities to a lack of ...social contacts, unemployment, and the consequences of stigmatisation. In empirical studies, social dysfunction is defined as a social performance measure, commonly based on the principles of cognitivism, and usually evaluated in laboratory and everyday settings. In schizophrenia, it is thought to be caused by cognitive dysfunction, related to brain dysfunction. From a medical perspective, schizophrenia is understood as a neurodevelopmental disorder resulting in a pattern of disconnection between important brain areas. Nevertheless, measures of neurocognition do not explain the expected amount of variance in social functioning. Other explanatory models of social dysfunction include structural functionalism, symbolic interactionism, and clinical phenomenology. Phenomenological accounts relate to the classical tradition in psychopathology, which describes schizophrenia as being marked by a certain “Gestalt”, which is in turn recognised as a distinctive and pervasive change in an individual’s self-experience and attunement to the surrounding world, thus emphasising the subjective experience of others. In the present paper, we intend to empirically explore the dilemma concerning the causes of social dysfunction in schizophrenia and to show how the comprehension, gained via a neuroscientific approach to a complex brain phenomenon can be meaningfully expanded by adding insights from different explanatory models. These models need to be operationalised so that all the data can be incorporated into a comprehensive statistical analysis.
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