Sažetak sa skupa
https://doi.org/10.21857/ypn4oc4189
Functional imaging of associative areas of the cerebral cortex
Jelena Božek
orcid.org/0000-0002-5986-5442
; University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia
*
Marko Radoš
; Clinical Department of Diagnostic and Interventional Neuroradiology, Clinical Hospital Center Zagreb, Zagreb, Croatia
Milan Radoš
; Croatian Institute for Brain Research, Faculty of Medicine, University of Zagreb, Zagreb, Croatia
* Dopisni autor.
Sažetak
Brain imaging using functional magnetic resonance imaging (fMRI) enables the study of functional connectivity between different brain regions at rest, when the individual is not performing a specific task. Resting-state functional connectivity analysis has become a key tool in neuroscientific research of psychological and neurological disorders. The ability to observe how different brain regions communicate, as well as how these connections can be disrupted in various disorders, opens new horizons for understanding, diagnosing, and potentially treating these conditions.
In Alzheimer’s disease, reduced connectivity in the Default Mode Network (DMN) affects memory processes, while in Parkinson’s disease, reduced connectivity in dopaminergic networks impairs motor functions. In autism, decreased connectivity between temporal and frontal regions explains difficulties in social interaction, and in ADHD, reduced connectivity between prefrontal regions and other areas of the brain is linked to problems with attention and impulsivity. In depression, reduced connectivity in networks for emotional regulation, such as prefrontal and limbic areas, may help in understanding the disorder. For anxiety disorders and PTSD, changes in the connectivity of the amygdala with prefrontal regions explain hyperreactivity to stress.
In patients with schizophrenia, it has been shown that the functional connectivity of the thalamus and the primary motor and somatosensory cortex is increased, while the functional connectivity of the thalamus and the prefrontal cortex, striatum and cerebellum is reduced (Murray and Antičević 2017.). Recent research shows that the functional architecture of neural networks can be used as a neuroradiological biomarker for the recognition of mental disorders including schizophrenia (Spronk et al. 2021). Although at this moment the sensitivity and specificity of fMRI-based diagnostics are not satisfactory for clinical use, it is likely that with the development of MRI protocols and post-processing analysis the problem will be solved in the future.
Recent advancements in neuroimaging have also provided valuable insights into the auditory language comprehension and intrinsic network abnormalities associated with Autism Spectrum Disorder (ASD). Hua et al. (2024) conducted an ALE meta-analysis of fMRI studies to investigate auditory language processing among children and adolescents with ASD, revealing altered brain activity in key regions involved in speech and language. Similarly, Goodwill et al. (2023) employed meta-analytic connectivity modeling to examine functional connectivity patterns in ASD, uncovering disruptions in neural circuits that underlie social and cognitive functioning. In another study, Yoon et al. (2024) utilized independent component analysis to explore intrinsic network abnormalities in children with ASD, providing evidence of atypical connectivity within brain networks implicated in sensory processing and executive functions. These studies provide deeper insight into the neural mechanisms underlying language and social cognition in individuals with ASD, offering potential targets for future therapeutic interventions. Ongoing research in this field promises to enhance our understanding of neurological disorders and pave the way for the development of targeted therapies based on functional brain networks.
Ključne riječi
Autism Spectrum Disorder; functional MRI; Schizophrenia
Hrčak ID:
333465
URI
Datum izdavanja:
25.6.2025.
Posjeta: 402 *