Bipolar Disorder
Curr Opin Neurobiol. 2023 Dec;83:102801. doi: 10.1016/j.conb.2023.102801. Epub 2023 Oct 27.ABSTRACTThis review focuses on recent advances made towards understanding the neurobiology of bipolar disorder (BD), a chronic neuropsychiatric illness characterized by altered mood and energy states. The past few years have seen the completion of the largest genetic studies by far, which have emphasized the polygenic nature of BD as well as it's connection to other psychiatric illnesses. Furthermore, the use of inducible pluripotent stem cells has rapidly expanded. These studies support previous work that implicates dysregulation of...
Source: Current Opinion in Neurobiology - January 15, 2024 Category: Neurology Authors: Madeline R Scott Colleen A McClung Source Type: research
Editorial overview: Motor circuits in action
Curr Opin Neurobiol. 2024 Jan 10;84:102836. doi: 10.1016/j.conb.2023.102836. Online ahead of print.NO ABSTRACTPMID:38211401 | DOI:10.1016/j.conb.2023.102836 (Source: Current Opinion in Neurobiology)
Source: Current Opinion in Neurobiology - January 11, 2024 Category: Neurology Authors: Dawn Blitz Sten Grillner Source Type: research
Cells, pathways, and models in dyskinesia research
Curr Opin Neurobiol. 2024 Jan 6;84:102833. doi: 10.1016/j.conb.2023.102833. Online ahead of print.ABSTRACTL-DOPA-induced dyskinesia (LID) is the most common form of hyperkinetic movement disorder resulting from altered information processing in the cortico-basal ganglia network. We here review recent advances clarifying the altered interplay between striatal output pathways in this movement disorder. We also review studies revealing structural and synaptic changes to the striatal microcircuitry and altered cortico-striatal activity dynamics in LID. We furthermore highlight the recent progress made in understanding the invo...
Source: Current Opinion in Neurobiology - January 7, 2024 Category: Neurology Authors: M Angela Cenci Arvind Kumar Source Type: research
Cells, pathways, and models in dyskinesia research
Curr Opin Neurobiol. 2024 Jan 6;84:102833. doi: 10.1016/j.conb.2023.102833. Online ahead of print.ABSTRACTL-DOPA-induced dyskinesia (LID) is the most common form of hyperkinetic movement disorder resulting from altered information processing in the cortico-basal ganglia network. We here review recent advances clarifying the altered interplay between striatal output pathways in this movement disorder. We also review studies revealing structural and synaptic changes to the striatal microcircuitry and altered cortico-striatal activity dynamics in LID. We furthermore highlight the recent progress made in understanding the invo...
Source: Current Opinion in Neurobiology - January 7, 2024 Category: Neurology Authors: M Angela Cenci Arvind Kumar Source Type: research
Cells, pathways, and models in dyskinesia research
Curr Opin Neurobiol. 2024 Jan 6;84:102833. doi: 10.1016/j.conb.2023.102833. Online ahead of print.ABSTRACTL-DOPA-induced dyskinesia (LID) is the most common form of hyperkinetic movement disorder resulting from altered information processing in the cortico-basal ganglia network. We here review recent advances clarifying the altered interplay between striatal output pathways in this movement disorder. We also review studies revealing structural and synaptic changes to the striatal microcircuitry and altered cortico-striatal activity dynamics in LID. We furthermore highlight the recent progress made in understanding the invo...
Source: Current Opinion in Neurobiology - January 7, 2024 Category: Neurology Authors: M Angela Cenci Arvind Kumar Source Type: research
Editorial overview: Computational neuroscience as a bridge between artificial intelligence, modeling and data
Curr Opin Neurobiol. 2024 Jan 5;84:102835. doi: 10.1016/j.conb.2023.102835. Online ahead of print.NO ABSTRACTPMID:38183889 | DOI:10.1016/j.conb.2023.102835 (Source: Current Opinion in Neurobiology)
Source: Current Opinion in Neurobiology - January 6, 2024 Category: Neurology Authors: Pietro Verzelli Tatjana Tchumatchenko Jeanette Hellgren Kotaleski Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
Unsupervised learning of mid-level visual representations
Curr Opin Neurobiol. 2023 Dec 27;84:102834. doi: 10.1016/j.conb.2023.102834. Online ahead of print.ABSTRACTRecently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become ...
Source: Current Opinion in Neurobiology - December 28, 2023 Category: Neurology Authors: Giulio Matteucci Eugenio Piasini Davide Zoccolan Source Type: research
The epigenome under pressure: On regulatory adaptation to chronic stress in the brain
Curr Opin Neurobiol. 2023 Dec 22;84:102832. doi: 10.1016/j.conb.2023.102832. Online ahead of print.ABSTRACTChronic stress (CS) can have long-lasting consequences on behavior and cognition, that are associated with stable changes in gene expression in the brain. Recent work has examined the role of the epigenome in the effects of CS on the brain. This review summarizes experimental evidence in rodents showing that CS can alter the epigenome and the expression of epigenetic modifiers in brain cells, and critically assesses their functional effect on genome function. It discusses the influence of the developmental time of str...
Source: Current Opinion in Neurobiology - December 23, 2023 Category: Neurology Authors: Rodrigo G Arzate-Mejia Nancy V N Carullo Isabelle M Mansuy Source Type: research
