The brain, a remarkable and intricate system, plays a fundamental role in shaping our behavior, encompassing cognitive and emotional processes (1–3). Understanding its structural and functional organization has been greatly enhanced through the utilization of neuroimaging and brain stimulation techniques. These powerful tools not only provide insights into the complex workings of the brain but also hold promise as potential therapeutic interventions for mental disorders (4). By leveraging these techniques, researchers gain valuable insights into the underlying mechanisms of mental disorders and their potential treatments. The combination of neuroimaging and brain stimulation holds great promise for accelerating the development of symptomatic therapies and introducing novel treatments to patients. To delve deeper into the mechanisms of neuropsychiatric disorders, researchers utilize various neuroimaging techniques, such as structural and functional magnetic resonance imaging (s/fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT), all of which offer detailed visualizations and measurements of brain structure, function, and chemistry (5). These tools are essential in several areas: identifying targets for intervention, guiding neurosurgical planning, determining optimal stimulator placement, and confirming post-operative procedure effectiveness.
Neuroimaging also assists with pre-treatment screening to identify potential responders and post-treatment evaluation to assess changes in brain circuitry associated with clinical outcomes. Researchers have used multimodal neuroimaging tools to find new neurobiological mechanisms behind neuropathogenesis, stimulation effects, brain responses, and the effectiveness of therapies. More attention has been paid to altered brain regions like the prefrontal cortex (PFC), which is involved in executive functions, emotional regulation, and making decisions. Several neuropsychiatric disorders (6–8) have been linked to this brain region. Neuroimaging studies have revealed structural and functional alterations in the PFC in conditions such as depression, schizophrenia, and addiction (9–11). Understanding these alterations and their relationship to disease mechanisms is crucial for developing targeted interventions (12–14).
Brain stimulation techniques, including invasive (e.g., deep brain stimulation) and non-invasive methods (e.g., transcranial magnetic stimulation [TMS], transcranial current stimulation [tCS]), aim to modulate neural activity in specific brain regions and circuits. Non-invasive brain stimulation techniques (NIBS) like TMS and tCS have gained attention in neuropsychiatry as they offer a safe and non-surgical approach to manipulate neural circuits involved in neuropsychiatric disorders. NIBS allows precise targeting of specific brain regions by placing the stimulation device over a particular area of the scalp. For instance, in depression treatment, stimulating the dorsolateral PFC can alleviate depressive symptoms by modulating mood regulation (15, 16). These techniques are customizable to an individual's unique characteristics, enhancing their potential in clinical practice.
Recent studies highlight distinct patterns of neural activity associated with various neuropsychiatric disorders, characterized by specific frequency bands. Personalized brain stimulation techniques utilize this knowledge to adjust stimulation parameters (e.g., frequency and intensity) and target specific frequency bands related to individual symptoms (17, 18). This personalized approach shows promise in improving treatment outcomes for patients with neuropsychiatric disorders. Combining NIBS with neuroimaging methods like fMRI and EEG helps researchers gain insights into brain stimulation's effects on neural activity and connectivity between brain regions (19, 20). These techniques have shown potential in treating neuropsychiatric disorders such as depression, obsessive-compulsive disorder, epilepsy, Alzheimer's disease (AD), and Parkinson's disease (PD).
This Research Topic is dedicated to showcasing exceptional cases of patients or individuals with unexpected or unusual diagnoses, treatment outcomes, or clinical courses. These case reports offer valuable insights into the neural underpinnings of various conditions, such as differential diagnosis, abnormal emotional processes, learning mechanisms, decision-making, and the clinical management of unique cases. They serve as essential educational tools, providing novel perspectives for neuroimaging and brain stimulation studies. Proudly presenting seven papers, this collection represents a significant advancement in the field of neuroimaging and brain stimulation, contributing to our understanding of complex neurological conditions and enhancing patient care.
Five case reports focus on depression and its association with other conditions. Finding effective treatment options for patients with treatment-resistant depression is the current challenge. Rymaszewska et al. present a treatment approach for treatment-resistant depression involving combined pharmacotherapy, psychotherapy, and various neurostimulation techniques, including deep brain stimulation of the medial forebrain bundle. Another challenge involves improving early identification and intervention for atypical and early-onset AD and discovering novel pharmacological treatment targets for both AD and depression. Liu et al. present a rare case where early-onset AD initially manifested as depression, emphasizing the importance of considering AD in depression's differential diagnosis. Chang et al. explore the application of repetitive TMS to the PFC and auditory cortex, shedding light on potential therapeutic interventions for patients with tinnitus and depression. Kim et al. present a single-case study investigating clinical and functional connectivity characteristics of antidepressant-induced mania in panic disorder. Understanding mania risk factors in panic disorder is crucial due to a 20–40% risk of inducing mania during treatment with antidepressants. The study suggests that altered amygdala-based resting-state functional connectivity could serve as a potential biomarker for identifying antidepressant-induced mania in panic disorder patients. Zakia and Iskandar highlight the challenge of diagnosing and treating co-occurring psychological symptoms and rare medical conditions, like intracranial tuberculoma, particularly in cases of peripartum-onset depressive disorder. The study presents a unique clinical scenario where a depressive disorder during the peripartum period masks the presence of a suspected intracranial tuberculoma.
Another case report discusses the association between reversible splenial lesion syndrome (RESLES) and mental disorders, particularly in bipolar II disorder. Understanding the underlying mechanisms and effective treatments for RESLES in bipolar II disorder are current challenges. Zhou et al. highlight a potential link between bipolar disorder and RESLES, particularly during hypomanic episodes. Creating efficient diagnostic and therapeutic approaches that can specifically target the structural changes in the brain is one of the current challenges in the study of PD. Nyatega et al. provide insights into the structural brain changes associated with PD by investigating gray matter, white matter, and cerebrospinal fluid abnormalities in PD using voxel-based morphometry.
The combination of neuroimaging and brain stimulation techniques in neuropsychiatry offers a synergistic advantage. Neuroimaging provides a comprehensive understanding of brain function and circuitry, shedding light on the intricate mechanisms underlying neuropsychiatric disorders. Concurrently, brain stimulation allows targeted intervention, manipulating specific brain regions or networks implicated in these disorders (21–23). Integrating neuroimaging and brain stimulation helps elucidate the neural underpinnings of neuropsychiatric disorders and optimize treatment strategies. This powerful combination accelerates the development of symptomatic therapies by identifying neural circuits involved and guiding precise therapeutic interventions (4). It holds the potential to revolutionize bioelectronic medicine, paving the way for personalized treatments and transformative advances in neuropsychiatric care (17, 18, 23).
Neuroimaging and brain stimulation are not exclusive to the clinical arena. Preclinical research utilizing animal models has explored the interplay of various factors involved in mental illnesses, such as genetic, environmental, and pharmacological manipulations, shedding light on disease phenotypes and underlying pathology (2, 24–36). These models simulate disease conditions, allowing researchers to assess symptomatology and evaluate potential interventions (37, 38). They provide valuable insights into disease mechanisms, testing of treatments, and therapeutic efficacy, as well as structural changes and imaging techniques for clinical cases (39–43). The combination of preclinical and clinical research contributes to the development of innovative therapeutics and personalized medicine (44–54).
In summary, neuroimaging and brain stimulation are powerful tools in the treatment of neuropsychiatric disorders. The integration of these techniques enables a deeper understanding of the pathophysiology of these disorders and facilitates the development of more effective therapies. By combining their strengths, researchers can potentially enhance the lives of patients by bringing new and personalized treatments to the forefront of neuropsychiatric care. We hope that this Research Topic has provided valuable insights into the neural underpinnings of differential diagnosis, abnormal emotional processes, learning mechanisms, decision-making, and the clinical management of unusual cases. We thank all the authors who contributed to this collection and the reviewers who provided valuable feedback. We look forward to future contributions that will continue to advance the field of Neuroimaging and Stimulation.
Author contributions
SB: Conceptualization, Writing—review and editing. AS: Conceptualization, Writing—review and editing. SH: Conceptualization, Writing—review and editing. MT: Conceptualization, Writing—original draft, Writing—review and editing.
Funding Statement
This work supported by #NEXTGENERATIONEU (NGEU) and funded by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006)—A multiscale integrated approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022) to SB and by OTKA-138125-K, TUDFO/47138-1/2019-ITM, ELKH-SZTE E's Lorand Research Network, and the University of Szeged to MT.
Abbreviations
AD, Alzheimer's disease; PFC, prefrontal cortex; NIBS, non-invasive brain stimulation techniques; PD, Parkinson's disease; RESLES, reversible splenial lesion syndrome; tCS, transcranial current stimulation; TMS, transcranial magnetic stimulation.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
- 1.Tanaka M, Telegdy G. Involvement of adrenergic and serotonergic receptors in antidepressant 124 like effect of urocortin 3 in a modified forced swimming test in mice. Brain Res Bull. (2008) 77:301–5. 10.1016/j.brainresbull.2008.08.012 [DOI] [PubMed] [Google Scholar]
- 2.Tanaka M, Kádár K, Tóth G, Telegdy G. Antidepressant-like effects of urocortin 3 fragments. 127 Brain Res Bull. (2011) 84:414–8. 10.1016/j.brainresbull.2011.01.016 [DOI] [PubMed] [Google Scholar]
- 3.Palotai M, Telegdy G, Tanaka M, Bagosi Z, Jászberényi M. Neuropeptide AF induces anxiety- like and antidepressant-like behavior in mice. Behav Brain Res. (2014) 274:264–9. 130 10.1016/j.bbr.2014.08.007 [DOI] [PubMed] [Google Scholar]
- 4.Tanaka M, Diano M, Battaglia S. Editorial: Insights into structural and functional organization of the brain: evidence from neuroimaging and non-invasive brain stimulation techniques. Front Psychiatry. (2023) 14:1225755. 10.3389/fpsyt.2023.1225755 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lu FM, Yuan Z. PET/SPECT molecular imaging in clinical neuroscience: recent advances in the investigation of CNS diseases. Quant Imaging Med Surg. (2015) 5:433–47. 10.3978/j.issn.2223-4292.2015.03.16 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Battaglia S, Harrison BJ, Fullana MA. Does the human ventromedial prefrontal cortex support fear learning, fear extinction or both? A commentary on subregional contributions. Mol Psychiatry. (2022) 27:784–6. 10.1038/s41380-021-01326-4 [DOI] [PubMed] [Google Scholar]
- 7.Battaglia S, Cardellicchio P, Di Fazio C, Nazzi C, Fracasso A, Borgomaneri S. Stopping in (e)motion: reactive action inhibition when facing valence-independent emotional stimuli. Front Behav Neurosci. (2022) 16:998714. 10.3389/fnbeh.2022.998714 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Battaglia S, Cardellicchio P, Di Fazio C, Nazzi C, Fracasso A, Borgomaneri S. The influence of vicarious fear-learning in “infecting” reactive action inhibition. Front Behav Neurosci. (2022) 16:946263. 10.3389/fnbeh.2022.946263 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Benussi A, Premi E, Gazzina S, Cantoni V, Cotelli MS, Giunta M, et al. Neurotransmitter imbalance dysregulates brain dynamic fluidity in frontotemporal degeneration. Neurobiol Aging. (2020) 94:176–84. 10.1016/j.neurobiolaging.2020.05.017 [DOI] [PubMed] [Google Scholar]
- 10.Premi E, Calhoun VD, Diano M, Gazzina S, Cosseddu M, Alberici A, et al. The inner fluctuations of the brain in pre-symptomatic frontotemporal dementia: the chronnectome fingerprint. Neuroimage. (2019) 189:645–54. 10.1016/j.neuroimage.2019.01.080 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Xie Y, Guan M, Cai Y, Wang Z, Ma Z, Fang P, et al. Impact of low-frequency repetitive transcranial magnetic stimulation on functional network connectivity in schizophrenia patients with auditory verbal hallucinations. Psychiatry Res. (2023) 320:114974. 10.1016/j.psychres.2022.114974 [DOI] [PubMed] [Google Scholar]
- 12.Battaglia S, Nazzi C, Thayer JF. Fear-induced bradycardia in mental disorders: Foundations, current advances, future perspectives. Neurosci Biobehav Rev. (2023) 149:105163. 10.1016/j.neubiorev.2023.105163 [DOI] [PubMed] [Google Scholar]
- 13.Battaglia S, Di Fazio C, Vicario CM, Avenanti A. Neuropharmacological modulation of N-methyl-D-aspartate, noradrenaline and endocannabinoid receptors in fear extinction learning: synaptic transmission and plasticity. Int J Mol Sci. (2023) 24:5926. 10.3390/ijms24065926 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Battaglia S, Garofalo S, di Pellegrino G, Starita F. Revaluing the role of vmPFC in the acquisition of pavlovian threat conditioning in humans. J Neurosci. (2020) 40:8491–500. 10.1523/JNEUROSCI.0304-20.2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Borgomaneri S, Battaglia S, Sciamanna G, Tortora F, Laricchiuta D. Memories are not written in stone: re-writing fear memories by means of non-invasive brain stimulation and optogenetic manipulations. Neurosci Biobehav Rev. (2021) 127:334–52. 10.1016/j.neubiorev.2021.04.036 [DOI] [PubMed] [Google Scholar]
- 16.Battaglia MR, Di Fazio C, Battaglia S. Activated tryptophan-kynurenine metabolic system in the human brain is associated with learned fear. Front Mol Neurosci. (2023) 6:7090. 10.3389/fnmol.2023.1217090 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Di Gregorio F, La Porta F, Petrone V. Accuracy of EEG biomarkers in the detection of clinical outcome in disorders of consciousness after severe acquired brain injury: preliminary results of a pilot study using a machine learning approach. Biomedicines. (2022) 10:1897. 10.3390/biomedicines10081897 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ippolito G, Bertaccini R, Tarasi L, Di Gregorio F, Trajkovic J, Battaglia S, et al. The role of alpha oscillations among the main neuropsychiatric disorders in the adult and developing human brain: evidence from the last 10 years of research. Biomedicines. (2022) 10:3189. 10.3390/biomedicines10123189 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Joyce DW, Kormilitzin A, Smith KA, Cipriani A. Explainable artificial intelligence for mental health through transparency and interpretability for understandability. NPJ Digit Med. (2023) 6:6. 10.1038/s41746-023-00751-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Celeghin A, Diano M, Bagnis A, Viola M, Tamietto M. Basic emotions in human neuroscience: neuroimaging and beyond. Front Psychol. (2017) 8:1432. 10.3389/fpsyg.2017.01432 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Battaglia S, Thayer JF. Functional interplay between central and autonomic nervous systems in human fear conditioning. Trends Neurosci. (2022) 45:504–6. 10.1016/j.tins.2022.04.003 [DOI] [PubMed] [Google Scholar]
- 22.Battaglia S, Orsolini S, Borgomaneri S, Barbieri R, Diciotti S, di Pellegrino G. Characterizing cardiac autonomic dynamics of fear learning in humans. Psychophysiology. (2022) 3:e14122. 10.1111/psyp.14122 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Di Gregorio, F Battaglia, S. Advances in EEG-based functional connectivity approaches to study central nervous system in health and disease. Adv Clin Exp Med. (2023) 32:607–12. 10.17219/acem/166476 [DOI] [PubMed] [Google Scholar]
- 24.Tanaka M, Szabó Á, Vécsei L. Integrating armchair, bench, and bedside research for behavioral neurology and neuropsychiatry: editorial. Biomedicines. (2022) 10:2999. 10.3390/biomedicines10122999 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Telegdy G, Adamik A, Tanaka M, Schally AV. Effects of the LHRH antagonist cetrorelix on affective and cognitive functions in rats. Regul Pept. (2010) 159:142–7. 10.1016/j.regpep.2009.08.005 [DOI] [PubMed] [Google Scholar]
- 26.Tanaka M, Schally AV, Telegdy G. Neurotransmission of the antidepressant-like effects of the growth hormone-releasing hormone antagonist MZ-4-71. Behav Brain Res. (2012) 228:388–91. 10.1016/j.bbr.2011.12.022 [DOI] [PubMed] [Google Scholar]
- 27.Tanaka M, Telegdy G. Neurotransmissions of antidepressant-like effects of neuromedin U-23 in mice. Behav Brain Res. (2014) 259:196–9. 10.1016/j.bbr.2013.11.005 [DOI] [PubMed] [Google Scholar]
- 28.Telegdy G, Tanaka M, Schally AV. Effects of the growth hormone-releasing hormone (GH-RH) antagonist on brain functions in mice. Behav Brain Res. (2011) 224:155–8. 10.1016/j.bbr.2011.05.036 [DOI] [PubMed] [Google Scholar]
- 29.Tanaka M, Csabafi K, Telegdy G. Neurotransmissions of antidepressant-like effects of kisspeptin-13. Regul Pept. (2013) 180:1–4. 10.1016/j.regpep.2012.08.017 [DOI] [PubMed] [Google Scholar]
- 30.Rákosi K, Masaru T, Zarándia M, Telegdy G, Tóth GK. Short analogs and mimetics of human urocortin 3 display antidepressant effects in vivo. Peptides. (2014) 62:59–66. 10.1016/j.peptides.2014.09.023 [DOI] [PubMed] [Google Scholar]
- 31.Tanaka M, Vécsei L. Editorial of special issue 'dissecting neurological and neuropsychiatric diseases: neurodegeneration and neuroprotection'. Int J Mol Sci. (2022) 23:6991. 10.3390/ijms23136991 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Tran KN, Nguyen NPK, Nguyen LTH, Shin HM, Yang IJ. Screening for neuroprotective and rapid antidepressant-like effects of 20 essential oils. Biomedicines. (2023) 11:1248. 10.3390/biomedicines11051248 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Baliellas DEM, Barros MP, Vardaris CV, Guariroba M, Poppe SC, Martins MF, et al. Propentofylline improves thiol-based antioxidant defenses and limits lipid peroxidation following gliotoxic injury in the rat brainstem. Biomedicines. (2023) 11:1652. 10.3390/biomedicines11061652 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Montanari M, Imbriani P, Bonsi P, Martella G, Peppe A. Beyond the microbiota: understanding the role of the enteric nervous system in Parkinson's disease from mice to human. Biomedicines. (2023) 11:1560. 10.3390/biomedicines11061560 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Garifulin R, Davleeva M, Izmailov A, Fadeev F, Markosyan V, Shevchenko R, et al. Evaluation of the autologous genetically enriched leucoconcentrate on the lumbar spinal cord morpho-functional recovery in a mini pig with thoracic spine contusion injury. Biomedicines. (2023) 11:1331. 10.3390/biomedicines11051331 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Bueno CRS, Tonin MCC, Buchaim DV, Barraviera B, Ferreira Junior RS, Santos PSDS, et al. Morphofunctional Improvement of the Facial Nerve and Muscles with Repair Using Heterologous Fibrin Biopolymer and Photobiomodulation. Pharmaceuticals. (2023) 16:653. 10.3390/ph16050653 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Tanaka M, Spekker E, Szabó Á, Polyák H, Vécsei L. Modelling the neurodevelopmental pathogenesis in neuropsychiatric disorders. Bioactive kynurenines and their analogues as neuroprotective agents-in celebration of 80th birthday of Professor Peter Riederer. J Neural Transm. (2022) 129:627–42. 10.1007/s00702-022-02513-5 [DOI] [PubMed] [Google Scholar]
- 38.Polyák H, Galla Z, Nánási N, Cseh EK, Rajda C, Veres G, et al. The tryptophan-kynurenine metabolic system is suppressed in cuprizone-induced model of demyelination simulating progressive multiple sclerosis. Biomedicines. (2023) 11:945. 10.3390/biomedicines11030945 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Sobolewska-Nowak J, Wachowska K, Nowak A, Orzechowska A, Szulc A, Płaza O, et al. Exploring the heart–mind connection: unraveling the shared pathways between depression and cardiovascular diseases. Biomedicines. (2023) 11:1903. 10.3390/biomedicines11071903 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Tug E, Fidan I, Bozdayi G, Yildirim F, Tunccan OG, Lale Z, et al. The relationship between the clinical course of SARS-CoV-2 infections and ACE2 and TMPRSS2 expression and polymorphisms. Adv Clin Exp Med. (2023) 3:409. 10.17219/acem/163409 [DOI] [PubMed] [Google Scholar]
- 41.Fan P, Miranda O, Qi X, Kofler J, Sweet RA, Wang L. Unveiling the enigma: exploring risk factors and mechanisms for psychotic symptoms in Alzheimer's disease through electronic medical records with deep learning models. Pharmaceuticals. (2023) 16:911. 10.3390/ph16070911 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Festa F, Medori S, Macrì M. Move your body, boost your brain: the positive impact of physical activity on cognition across all age groups. Biomedicines. (2023) 11:1765. 10.3390/biomedicines1106176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Alhaddad A, Radwan A, Mohamed NA. Mehanna, ET, Mostafa YM, et al. Rosiglitazone mitigates dexamethasone-induced depression in mice via modulating brain glucose metabolism and AMPK/mTOR signaling pathway. Biomedicines. (2023) 11:860. 10.3390/biomedicines11030860 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Statsenko Y, Habuza T, Smetanina D, Simiyu GL, Meribout S, King FC, et al. Unraveling lifelong brain morphometric dynamics: a protocol for systematic review and meta-analysis in healthy neurodevelopment and ageing. Biomedicines. (2023) 11:1999. 10.3390/biomedicines11071999 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Dang J, Tao Q, Niu X, Zhang M, Gao X, Yang Z, et al. Meta-analysis of structural and functional brain abnormalities in cocaine addiction. Front Psychiatry. (2022) 13:927075. 10.3389/fpsyt.2022.927075 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Okanda Nyatega C, Qiang L, Jajere Adamu M, Bello Kawuwa H. Altered striatal functional connectivity and structural dysconnectivity in individuals with bipolar disorder: A resting state magnetic resonance imaging study. Front Psychiatry. (2022) 13:1054380. 10.3389/fpsyt.2022.1054380 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Du H, Yang B, Wang H, Zeng Y, Xin J, Li X. The non-linear correlation between the volume of cerebral white matter lesions and incidence of bipolar disorder: a secondary analysis of data from a cross-sectional study. Front Psychiatry. (2023) 14:1149663. 10.3389/fpsyt.2023.1149663 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Chen Y, Yu R, DeSouza JFX, Shen Y, Zhang H, Zhu C, et al. Differential responses from the left postcentral gyrus, right middle frontal gyrus, and precuneus to meal ingestion in patients with functional dyspepsia. Front Psychiatry. (2023) 14:1184797. 10.3389/fpsyt.2023.1184797 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Adamu MJ, Qiang L, Nyatega CO, Younis A, Kawuwa HB, Jabire AH, et al. Unraveling the pathophysiology of schizo-phrenia: insights from structural magnetic resonance imaging studies. Front Psychiatry. (2023) 14:1188603. 10.3389/fpsyt.2023.1188603 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Veldema J. Non-invasive brain stimulation and sex/polypeptide hormones in reciprocal interactions: a systematic review. Biomedicines. (2023) 11:1981. 10.3390/biomedicines11071981 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Balogh L. Tanaka, M, Török N, Vécsei L, Taguchi S. Crosstalk between existential phenomenological psychotherapy and neurological sciences in mood and anxiety disorders. Biomedicines. (2021) 9:340. 10.3390/biomedicines9040340 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Hakamata Y, Hori H, Mizukami S, Izawa S, Yoshida F, Moriguchi Y, et al. Blunted diurnal interleukin-6 rhythm is associated with amygdala emotional hyporeactivity and depression: a modulating role of gene-stressor interactions. Front Psychiatry. (2023) 14:1196235. 10.3389/fpsyt.2023.1196235 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Rassler B, Blinowska K, Kaminski M, Pfurtscheller G. Analysis of respiratory sinus arrhythmia and directed information flow between brain and body indicate different management strategies of fMRI-related anxiety. Biomedicines. (2023) 11:1028. 10.3390/biomedicines11041028 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Vasiliu O. Efficacy, tolerability, and safety of toludesvenlafaxine for the treatment of major depressive disorder—A narrative review. Pharmaceuticals. (2023) 16:411. 10.3390/ph16030411 [DOI] [PMC free article] [PubMed] [Google Scholar]