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Tiesinga P, Platonov A, Pelliccia V, LoRusso G, Sartori I, Orban GA. Uncovering the fast, directional signal flow through the human temporal pole during semantic processing. Sci Rep 2023; 13:6831. [PMID: 37100843 PMCID: PMC10133264 DOI: 10.1038/s41598-023-33318-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 04/11/2023] [Indexed: 04/28/2023] Open
Abstract
The temporal pole (TP) plays a central role in semantic memory, yet its neural machinery is unknown. Intracerebral recordings in patients discriminating visually the gender or actions of an actor, yielded gender discrimination responses in the ventrolateral (VL) and tip (T) regions of right TP. Granger causality revealed task-specific signals travelling first forward from VL to T, under control of orbitofrontal cortex (OFC) and neighboring prefrontal cortex, and then, strongly, backwards from T to VL. Many other cortical regions provided inputs to or received outputs from both TP regions, often with longer delays, with ventral temporal afferents to VL signaling the actor's physical appearance. The TP response timing reflected more that of the connections to VL, controlled by OFC, than that of the input leads themselves. Thus, visual evidence for gender categories, collected by VL, activates category labels in T, and consequently, category features in VL, indicating a two-stage representation of semantic categories in TP.
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Affiliation(s)
- P Tiesinga
- Neuroinformatics Department, Faculty of Science, Radboud University, Heyendaalseweg 135, 6525AJ, Nijmegen, The Netherlands.
| | - A Platonov
- Department of Medicine and Surgery, University of Parma, Via Volturno 39/E, 43125, Parma, Italy
| | - V Pelliccia
- Claudio Munari Center for Epilepsy Surgery, Ospedale Niguarda-Ca' Granda, 20162, Milan, Italy
| | - G LoRusso
- Claudio Munari Center for Epilepsy Surgery, Ospedale Niguarda-Ca' Granda, 20162, Milan, Italy
| | - I Sartori
- Claudio Munari Center for Epilepsy Surgery, Ospedale Niguarda-Ca' Granda, 20162, Milan, Italy
| | - G A Orban
- Department of Medicine and Surgery, University of Parma, Via Volturno 39/E, 43125, Parma, Italy.
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Kirkels LAMH, Zhang W, Havenith MN, Tiesinga P, Glennon J, van Wezel RJA, Duijnhouwer J. The opto-locomotor reflex as a tool to measure sensitivity to moving random dot patterns in mice. Sci Rep 2018; 8:7710. [PMID: 29769564 PMCID: PMC5955912 DOI: 10.1038/s41598-018-25844-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 04/24/2018] [Indexed: 01/17/2023] Open
Abstract
We designed a method to quantify mice visual function by measuring reflexive opto-locomotor responses. Mice were placed on a Styrofoam ball at the center of a large dome on the inside of which we projected moving random dot patterns. Because we fixed the heads of the mice in space and the ball was floating on pressurized air, locomotion of the mice was translated to rotation of the ball, which we registered. Sudden onsets of rightward or leftward moving patterns caused the mice to reflexively change their running direction. We quantified the opto-locomotor responses to different pattern speeds, luminance contrasts, and dot sizes. We show that the method is fast and reliable and the magnitude of the reflex is stable within sessions. We conclude that this opto-locomotor reflex method is suitable to quantify visual function in mice.
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Affiliation(s)
- L A M H Kirkels
- Department of Biophysics, Donders Institute, Radboud University, Nijmegen, The Netherlands.
| | - W Zhang
- Department of Biophysics, Donders Institute, Radboud University, Nijmegen, The Netherlands
| | - M N Havenith
- Department of Neuroinformatics, Donders Institute, Radboud University, Nijmegen, The Netherlands.,Department of Cognitive Neuroscience, Donders Institute, RadboudUMC, Nijmegen, The Netherlands
| | - P Tiesinga
- Department of Neuroinformatics, Donders Institute, Radboud University, Nijmegen, The Netherlands
| | - J Glennon
- Department of Cognitive Neuroscience, Donders Institute, RadboudUMC, Nijmegen, The Netherlands
| | - R J A van Wezel
- Department of Biophysics, Donders Institute, Radboud University, Nijmegen, The Netherlands.,Biomedical Signals and Systems, MIRA, Twente University, Enschede, The Netherlands
| | - J Duijnhouwer
- Department of Biophysics, Donders Institute, Radboud University, Nijmegen, The Netherlands.,Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, USA
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Hassani SA, Oemisch M, Balcarras M, Westendorff S, Ardid S, van der Meer MA, Tiesinga P, Womelsdorf T. A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque. Sci Rep 2017; 7:40606. [PMID: 28091572 PMCID: PMC5238510 DOI: 10.1038/srep40606] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 12/08/2016] [Indexed: 01/05/2023] Open
Abstract
Noradrenaline is believed to support cognitive flexibility through the alpha 2A noradrenergic receptor (a2A-NAR) acting in prefrontal cortex. Enhanced flexibility has been inferred from improved working memory with the a2A-NA agonist Guanfacine. But it has been unclear whether Guanfacine improves specific attention and learning mechanisms beyond working memory, and whether the drug effects can be formalized computationally to allow single subject predictions. We tested and confirmed these suggestions in a case study with a healthy nonhuman primate performing a feature-based reversal learning task evaluating performance using Bayesian and Reinforcement learning models. In an initial dose-testing phase we found a Guanfacine dose that increased performance accuracy, decreased distractibility and improved learning. In a second experimental phase using only that dose we examined the faster feature-based reversal learning with Guanfacine with single-subject computational modeling. Parameter estimation suggested that improved learning is not accounted for by varying a single reinforcement learning mechanism, but by changing the set of parameter values to higher learning rates and stronger suppression of non-chosen over chosen feature information. These findings provide an important starting point for developing nonhuman primate models to discern the synaptic mechanisms of attention and learning functions within the context of a computational neuropsychiatry framework.
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Affiliation(s)
- S. A. Hassani
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - M. Oemisch
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - M. Balcarras
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - S. Westendorff
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
| | - S. Ardid
- Department of Mathematics, Boston University, Boston, MA 02215, USA
| | - M. A. van der Meer
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - P. Tiesinga
- Department of Neuroinformatics, Donders Centre for Neuroscience, Radboud University Nijmegen, Nijmegen, AJ 6525, The Netherlands
| | - T. Womelsdorf
- Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada
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Olde Loohuis NFM, Kole K, Glennon JC, Karel P, Van der Borg G, Van Gemert Y, Van den Bosch D, Meinhardt J, Kos A, Shahabipour F, Tiesinga P, van Bokhoven H, Martens GJM, Kaplan BB, Homberg JR, Aschrafi A. Elevated microRNA-181c and microRNA-30d levels in the enlarged amygdala of the valproic acid rat model of autism. Neurobiol Dis 2015; 80:42-53. [PMID: 25986729 DOI: 10.1016/j.nbd.2015.05.006] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2014] [Revised: 04/14/2015] [Accepted: 05/10/2015] [Indexed: 11/17/2022] Open
Abstract
Autism spectrum disorders are severe neurodevelopmental disorders, marked by impairments in reciprocal social interaction, delays in early language and communication, and the presence of restrictive, repetitive and stereotyped behaviors. Accumulating evidence suggests that dysfunction of the amygdala may be partially responsible for the impairment of social behavior that is a hallmark feature of ASD. Our studies suggest that a valproic acid (VPA) rat model of ASD exhibits an enlargement of the amygdala as compared to controls rats, similar to that observed in adolescent ASD individuals. Since recent research suggests that altered neuronal development and morphology, as seen in ASD, may result from a common post-transcriptional process that is under tight regulation by microRNAs (miRs), we examined genome-wide transcriptomics expression in the amygdala of rats prenatally exposed to VPA, and detected elevated miR-181c and miR-30d expression levels as well as dysregulated expression of their cognate mRNA targets encoding proteins involved in neuronal system development. Furthermore, selective suppression of miR-181c function attenuates neurite outgrowth and branching, and results in reduced synaptic density in primary amygdalar neurons in vitro. Collectively, these results implicate the small non-coding miR-181c in neuronal morphology, and provide a framework of understanding how dysregulation of a neurodevelopmentally relevant miR in the amygdala may contribute to the pathophysiology of ASD.
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Affiliation(s)
- N F M Olde Loohuis
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - K Kole
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - J C Glennon
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - P Karel
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - G Van der Borg
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Y Van Gemert
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - D Van den Bosch
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - J Meinhardt
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - A Kos
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - F Shahabipour
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - P Tiesinga
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - H van Bokhoven
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands; Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - G J M Martens
- Department of Molecular Animal Physiology, Donders Institute for Brain, Cognition and Behavior, Nijmegen Centre for Molecular Life Sciences (NCMLS), Radboud University Nijmegen, Nijmegen, The Netherlands
| | - B B Kaplan
- Laboratory of Molecular Biology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - J R Homberg
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - A Aschrafi
- Department of Neuroinformatics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.
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