Estimating the value of alternative options is a key process in decision-making. Human functional magnetic resonance imaging and monkey electrophysiology studies have identified brain regions, such as the ventromedial prefrontal cortex (vmPFC) and lateral orbitofrontal cortex (lOFC), composing a value system. In the present study, in an effort to bridge across species and techniques, we investigated the neural representation of value ratings in 36 people with epilepsy, using intracranial electroencephalography. We found that subjective value was positively reflected in both vmPFC and lOFC high-frequency activity, plus several other brain regions, including the hippocampus. We then demonstrated that subjective value could be decoded (1) in pre-stimulus activity, (2) for various categories of items, (3) even during a distractive task and (4) as both linear and quadratic signals (encoding both value and confidence). Thus, our findings specify key functional properties of neural value signals (anticipation, generality, automaticity, quadraticity), which might provide insights into human irrational choice behaviors.
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http://dx.doi.org/10.1038/s41593-020-0615-9 | DOI Listing |
J Transl Med
December 2024
Department of Neurology and National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Huashan Hospital, Fudan University, Shanghai, China.
Background: Epilepsy, as a chronic noncommunicable disease with recurrent seizures, may be a marker of deterioration or alteration in other underlying neurological diseases. This study aimed to investigate the relationship of epilepsy with brain function, other common brain disorders, and their underlying mechanisms.
Methods: The study was based on clinical diagnostic and test data from 426,527 participants in the UK Biobank, of whom 3,251 were diagnosed with epilepsy at baseline.
BMC Bioinformatics
December 2024
College of Computer and Information Engineering/College of Artificial Intelligence, Nanjing Tech University, Nanjing, 210093, China.
Background: The collection of substantial amounts of electroencephalogram (EEG) data is typically time-consuming and labor-intensive, which adversely impacts the development of decoding models with strong generalizability, particularly when the available data is limited. Utilizing sufficient EEG data from other subjects to aid in modeling the target subject presents a potential solution, commonly referred to as domain adaptation. Most current domain adaptation techniques for EEG decoding primarily focus on learning shared feature representations through domain alignment strategies.
View Article and Find Full Text PDFBMC Psychiatry
December 2024
Department of Geriatric Psychiatry, Suzhou Mental Health Center, Suzhou Guangji Hospital, the Affiliated Guangji Hospital of Soochow University, Suzhou, China.
Background: Cognitive impairment is prevalent in bipolar disorder (BD), and has negative impacts on functional impairments and quality of life, despite euthymic states in most individuals. The underlying neurobiological basis of cognitive impairment in BD is still unclear.
Methods: To further explore potential connectivity abnormalities and their associations with cognitive impairment, we conducted a degree centrality (DC) analysis and DC (seed)-based functional connectivity (FC) approach in unmedicated, euthymic individuals with BD.
Eur Arch Psychiatry Clin Neurosci
December 2024
IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Recent studies suggested that structural changes in the cerebellum are implicated in the pathophysiology of bipolar disorder (BD). Here, we aimed to characterize the structural alterations of cerebellar lobules in BD, evaluating their possible relation with those occurring in the rest of the brain. One-hundred-fifty-five type I BD patients were recruited and compared with one-hundred-nineteen controls subjects.
View Article and Find Full Text PDFNat Methods
December 2024
Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy.
Optical approaches to monitor neural activity are transforming neuroscience, owing to a fast-evolving palette of genetically encoded molecular reporters. However, the field still requires robust and label-free technologies to monitor the multifaceted biomolecular changes accompanying brain development, aging or disease. Here, we have developed vibrational fiber photometry as a low-invasive method for label-free monitoring of the biomolecular content of arbitrarily deep regions of the mouse brain in vivo through spontaneous Raman spectroscopy.
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