1
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Cracknell RO, Tavassoli T, Field DT. High-dose Vitamin-B6 reduces sensory over-responsivity. J Psychopharmacol 2024:2698811241271972. [PMID: 39180365 DOI: 10.1177/02698811241271972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/26/2024]
Abstract
BACKGROUND Sensory reactivity differences are experienced by between 5% and 15% of the population, often taking the form of sensory over-responsivity (SOR), in which sensory stimuli are experienced as unusually intense and everyday function is affected. A potential mechanism underlying over-responsivity is an imbalance between neural excitation and inhibition in which inhibitory influences are relatively weakened. Therefore, interventions that boost neural inhibition or reduce neural excitation may reduce SOR; Vitamin-B6 is the coenzyme for the conversion of excitatory glutamate to inhibitory gamma-aminobutyric acid (GABA), and in animal models, it both increases the concentration of GABA and reduces glutamate. AIMS To discover whether taking a high dose of Vitamin-B6 reduces SOR and other aspects of sensory reactivity. METHODS We recruited 300 adults (249 females) from the general population who completed the Sensory Processing 3-Dimensions Scale (SP-3D) first at baseline, and again following randomisation to either 1 month's supplementation with 100 mg Vitamin-B6, or one of two control conditions (1000 µg Vitamin-B12 or placebo). To focus on individuals who experience SOR, we analysed the effects of supplementation only on individuals with high baseline SOR scores (above the 87th percentile). RESULTS In individuals with SOR at baseline, Vitamin-B6 selectively reduced SOR compared to both placebo and Vitamin-B12. We also found that Vitamin-B6 selectively reduced postural disorder in individuals with high scores on this subscale at baseline, but there were no effects on the four remaining SP-3D subscales. CONCLUSIONS Clinical trials and mechanistic studies should now be conducted in autism, attention deficit hyperactivity disorder and other groups with SOR.
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Affiliation(s)
- Rebekah O Cracknell
- School of Psychology and Clinical Language Sciences, The University of Reading, Reading, Berkshire, UK
| | - Teresa Tavassoli
- School of Psychology and Clinical Language Sciences, The University of Reading, Reading, Berkshire, UK
| | - David T Field
- School of Psychology and Clinical Language Sciences, The University of Reading, Reading, Berkshire, UK
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2
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Nussinov R, Yavuz BR, Demirel HC, Arici MK, Jang H, Tuncbag N. Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide. Front Cell Dev Biol 2024; 12:1376639. [PMID: 39015651 PMCID: PMC11249571 DOI: 10.3389/fcell.2024.1376639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 06/10/2024] [Indexed: 07/18/2024] Open
Abstract
The connection and causality between cancer and neurodevelopmental disorders have been puzzling. How can the same cellular pathways, proteins, and mutations lead to pathologies with vastly different clinical presentations? And why do individuals with neurodevelopmental disorders, such as autism and schizophrenia, face higher chances of cancer emerging throughout their lifetime? Our broad review emphasizes the multi-scale aspect of this type of reasoning. As these examples demonstrate, rather than focusing on a specific organ system or disease, we aim at the new understanding that can be gained. Within this framework, our review calls attention to computational strategies which can be powerful in discovering connections, causalities, predicting clinical outcomes, and are vital for drug discovery. Thus, rather than centering on the clinical features, we draw on the rapidly increasing data on the molecular level, including mutations, isoforms, three-dimensional structures, and expression levels of the respective disease-associated genes. Their integrated analysis, together with chromatin states, can delineate how, despite being connected, neurodevelopmental disorders and cancer differ, and how the same mutations can lead to different clinical symptoms. Here, we seek to uncover the emerging connection between cancer, including pediatric tumors, and neurodevelopmental disorders, and the tantalizing questions that this connection raises.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Bengi Ruken Yavuz
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
| | | | - M. Kaan Arici
- Graduate School of Informatics, Middle East Technical University, Ankara, Türkiye
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, United States
| | - Nurcan Tuncbag
- Department of Chemical and Biological Engineering, Koc University, Istanbul, Türkiye
- School of Medicine, Koc University, Istanbul, Türkiye
- Koc University Research Center for Translational Medicine (KUTTAM), Istanbul, Türkiye
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3
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Damera SR, De Asis-Cruz J, Cook KM, Kapse K, Spoehr E, Murnick J, Basu S, Andescavage N, Limperopoulos C. Regional homogeneity as a marker of sensory cortex dysmaturity in preterm infants. iScience 2024; 27:109662. [PMID: 38665205 PMCID: PMC11043889 DOI: 10.1016/j.isci.2024.109662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/23/2024] [Accepted: 04/01/2024] [Indexed: 04/28/2024] Open
Abstract
Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.
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Affiliation(s)
- Srikanth R. Damera
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kevin M. Cook
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kushal Kapse
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Jon Murnick
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Sudeepta Basu
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
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4
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Vakilzadeh G, Maseko BC, Bartely TD, McLennan YA, Martínez-Cerdeño V. Increased number of excitatory synapsis and decreased number of inhibitory synapsis in the prefrontal cortex in autism. Cereb Cortex 2024; 34:121-128. [PMID: 38696601 PMCID: PMC11065106 DOI: 10.1093/cercor/bhad268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 06/15/2023] [Accepted: 07/16/2023] [Indexed: 05/04/2024] Open
Abstract
Previous studies in autism spectrum disorder demonstrated an increased number of excitatory pyramidal cells and a decreased number of inhibitory parvalbumin+ chandelier interneurons in the prefrontal cortex of postmortem brains. How these changes in cellular composition affect the overall abundance of excitatory and inhibitory synapses in the cortex is not known. Herein, we quantified the number of excitatory and inhibitory synapses in the prefrontal cortex of 10 postmortem autism spectrum disorder brains and 10 control cases. To identify excitatory synapses, we used VGlut1 as a marker of the presynaptic component and postsynaptic density protein-95 as marker of the postsynaptic component. To identify inhibitory synapses, we used the vesicular gamma-aminobutyric acid transporter as a marker of the presynaptic component and gephyrin as a marker of the postsynaptic component. We used Puncta Analyzer to quantify the number of co-localized pre- and postsynaptic synaptic components in each area of interest. We found an increase in the number of excitatory synapses in upper cortical layers and a decrease in inhibitory synapses in all cortical layers in autism spectrum disorder brains compared with control cases. The alteration in the number of excitatory and inhibitory synapses could lead to neuronal dysfunction and disturbed network connectivity in the prefrontal cortex in autism spectrum disorder.
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Affiliation(s)
- Gelareh Vakilzadeh
- Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine, Sacramento, CA, United States
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children, Sacramento, CA, United States
| | - Busisiwe C Maseko
- Faculty of health Sciences, School of Anatomical Sciences, University of the Witwatersrand, Johannesburg, The Republic of South Africa
| | - Trevor D Bartely
- Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine, Sacramento, CA, United States
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children, Sacramento, CA, United States
| | - Yingratana A McLennan
- Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine, Sacramento, CA, United States
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children, Sacramento, CA, United States
| | - Verónica Martínez-Cerdeño
- Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine, Sacramento, CA, United States
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children, Sacramento, CA, United States
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, United States
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5
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Sapey-Triomphe LA, Puts NAJ, Costa TL, Wagemans J. GABA and Glx predict EEG responses of visual sensitivity in autism. Autism Res 2024; 17:917-922. [PMID: 38576253 DOI: 10.1002/aur.3130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/21/2024] [Indexed: 04/06/2024]
Abstract
The mechanisms underlying atypical sensory processing in autism remain to be elucidated, but research points toward a role of the glutamatergic/GABAergic balance. To investigate the potential relationships between visual sensitivity and its molecular correlates in autism, we combined data from electroencephalography (EEG) and magnetic resonance spectroscopy (MRS) studies. Twenty autistic adults and sixteen neurotypical adults (NT) participated in both an EEG study assessing visual sensitivity (Sapey-Triomphe et al., Autism Research, 2023) and in an MRS study measuring Glx and GABA+ concentrations in the occipital cortex (Sapey-Triomphe et al., Molecular Autism, 2021). These studies revealed no group differences in neural detection thresholds or in Glx/GABA levels in the occipital cortex. Neural detection thresholds for contrast and spatial frequency (SF) were determined using fast periodic visual stimulations and neural frequency tagging. In the present study, Glx/GABA+ concentrations in the occipital cortex and neural detection thresholds did not differ between groups. Interestingly, lower Glx/GABA+ ratios were associated with lower contrast detection thresholds and higher SF detection thresholds. These correlations were also significant within the neurotypical and autistic groups. This report suggests that the Glx/GABA balance regulates visual detection thresholds across individuals. In both autistic and NTs, lower Glx/GABA ratios in the occipital cortex allow for better detection of visual inputs at the neural level. This study sheds light on the neurochemical underpinnings of visual sensitivity in autism and warrants further investigation.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, CAP Team, Bron, France
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences and the Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Thiago L Costa
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
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6
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Nahas LD, Datta A, Alsamman AM, Adly MH, Al-Dewik N, Sekaran K, Sasikumar K, Verma K, Doss GPC, Zayed H. Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions. Metab Brain Dis 2024; 39:29-42. [PMID: 38153584 PMCID: PMC10799794 DOI: 10.1007/s11011-023-01322-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 11/02/2023] [Indexed: 12/29/2023]
Abstract
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.
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Affiliation(s)
| | - Ankur Datta
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India
| | - Alsamman M Alsamman
- Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
| | - Monica H Adly
- Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
| | - Nader Al-Dewik
- Department of Research, Women's Wellness and Research Center, Hamad Medical Corporation, Doha, Qatar
| | - Karthik Sekaran
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India
- Center for Brain Research, Indian Institute of Science, Bengaluru, India
| | - K Sasikumar
- Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Kanika Verma
- Department of parasitology and host biology ICMR-NIMR, Dwarka, Delhi, India
| | - George Priya C Doss
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India
| | - Hatem Zayed
- Department of Biomedical Sciences College of Health Sciences, QU Health, Qatar University, Doha, Qatar.
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7
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Bhaskaran AA, Gauvrit T, Vyas Y, Bony G, Ginger M, Frick A. Endogenous noise of neocortical neurons correlates with atypical sensory response variability in the Fmr1 -/y mouse model of autism. Nat Commun 2023; 14:7905. [PMID: 38036566 PMCID: PMC10689491 DOI: 10.1038/s41467-023-43777-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023] Open
Abstract
Excessive neural variability of sensory responses is a hallmark of atypical sensory processing in autistic individuals with cascading effects on other core autism symptoms but unknown neurobiological substrate. Here, by recording neocortical single neuron activity in a well-established mouse model of Fragile X syndrome and autism, we characterized atypical sensory processing and probed the role of endogenous noise sources in exaggerated response variability in males. The analysis of sensory stimulus evoked activity and spontaneous dynamics, as well as neuronal features, reveals a complex cellular and network phenotype. Neocortical sensory information processing is more variable and temporally imprecise. Increased trial-by-trial and inter-neuronal response variability is strongly related to key endogenous noise features, and may give rise to behavioural sensory responsiveness variability in autism. We provide a novel preclinical framework for understanding the sources of endogenous noise and its contribution to core autism symptoms, and for testing the functional consequences for mechanism-based manipulation of noise.
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Affiliation(s)
- Arjun A Bhaskaran
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Théo Gauvrit
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Yukti Vyas
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Guillaume Bony
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Melanie Ginger
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Andreas Frick
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France.
- University of Bordeaux, 33000, Bordeaux, France.
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8
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Baker DH, Marinova D, Aveyard R, Hargreaves LJ, Renton A, Castellani R, Hall P, Harmens M, Holroyd G, Nicholson B, Williams EL, Hobson HM, Wade AR. Temporal dynamics of normalization reweighting. J Vis 2023; 23:6. [PMID: 37862008 PMCID: PMC10615141 DOI: 10.1167/jov.23.12.6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 09/08/2023] [Indexed: 10/21/2023] Open
Abstract
For decades, neural suppression in early visual cortex has been thought to be fixed. But recent work has challenged this assumption by showing that suppression can be reweighted based on recent history; when pairs of stimuli are repeatedly presented together, suppression between them strengthens. Here we investigate the temporal dynamics of this process using a steady-state visual evoked potential (SSVEP) paradigm that provides a time-resolved, direct index of suppression between pairs of stimuli flickering at different frequencies (5 and 7 Hz). Our initial analysis of an existing electroencephalography (EEG) dataset (N = 100) indicated that suppression increases substantially during the first 2-5 seconds of stimulus presentation (with some variation across stimulation frequency). We then collected new EEG data (N = 100) replicating this finding for both monocular and dichoptic mask arrangements in a preregistered study designed to measure reweighting. A third experiment (N = 20) used source-localized magnetoencephalography and found that these effects are apparent in primary visual cortex (V1), consistent with results from neurophysiological work. Because long-standing theories propose inhibition/excitation differences in autism, we also compared reweighting between individuals with high versus low autistic traits, and with and without an autism diagnosis, across our three datasets (total N = 220). We find no compelling differences in reweighting that are associated with autism. Our results support the normalization reweighting model and indicate that for prolonged stimulation, increases in suppression occur on the order of 2-5 seconds after stimulus onset.
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Affiliation(s)
- Daniel H Baker
- Department of Psychology and York Biomedical Research Institute, University of York, York, UK
| | | | | | | | - Alice Renton
- Department of Psychology, University of York, York, UK
| | | | - Phoebe Hall
- Department of Psychology, University of York, York, UK
| | | | | | | | | | - Hannah M Hobson
- Department of Psychology and York Biomedical Research Institute, University of York, York, UK
| | - Alex R Wade
- Department of Psychology and York Biomedical Research Institute, University of York, York, UK
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9
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Rosenberg A, Thompson LW, Doudlah R, Chang TY. Neuronal Representations Supporting Three-Dimensional Vision in Nonhuman Primates. Annu Rev Vis Sci 2023; 9:337-359. [PMID: 36944312 DOI: 10.1146/annurev-vision-111022-123857] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
The visual system must reconstruct the dynamic, three-dimensional (3D) world from ambiguous two-dimensional (2D) retinal images. In this review, we synthesize current literature on how the visual system of nonhuman primates performs this transformation through multiple channels within the classically defined dorsal (where) and ventral (what) pathways. Each of these channels is specialized for processing different 3D features (e.g., the shape, orientation, or motion of objects, or the larger scene structure). Despite the common goal of 3D reconstruction, neurocomputational differences between the channels impose distinct information-limiting constraints on perception. Convergent evidence further points to the little-studied area V3A as a potential branchpoint from which multiple 3D-fugal processing channels diverge. We speculate that the expansion of V3A in humans may have supported the emergence of advanced 3D spatial reasoning skills. Lastly, we discuss future directions for exploring 3D information transmission across brain areas and experimental approaches that can further advance the understanding of 3D vision.
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Affiliation(s)
- Ari Rosenberg
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA;
| | - Lowell W Thompson
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA;
| | - Raymond Doudlah
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA;
| | - Ting-Yu Chang
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
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10
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Noel JP, Angelaki DE. A theory of autism bridging across levels of description. Trends Cogn Sci 2023; 27:631-641. [PMID: 37183143 PMCID: PMC10330321 DOI: 10.1016/j.tics.2023.04.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/18/2023] [Accepted: 04/19/2023] [Indexed: 05/16/2023]
Abstract
Autism impacts a wide range of behaviors and neural functions. As such, theories of autism spectrum disorder (ASD) are numerous and span different levels of description, from neurocognitive to molecular. We propose how existent behavioral, computational, algorithmic, and neural accounts of ASD may relate to one another. Specifically, we argue that ASD may be cast as a disorder of causal inference (computational level). This computation relies on marginalization, which is thought to be subserved by divisive normalization (algorithmic level). In turn, divisive normalization may be impaired by excitatory-to-inhibitory imbalances (neural implementation level). We also discuss ASD within similar frameworks, those of predictive coding and circular inference. Together, we hope to motivate work unifying the different accounts of ASD.
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Affiliation(s)
- Jean-Paul Noel
- Center for Neural Science, New York University, New York, NY, USA.
| | - Dora E Angelaki
- Center for Neural Science, New York University, New York, NY, USA; Tandon School of Engineering, New York University, New York, NY, USA
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11
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Liu XY, Wang K, Deng XH, Wei YH, Guo R, Liu SF, Zhu YF, Zhong JJ, Zheng JY, Wang MD, Ye QH, He JQ, Guo KH, Zhu JR, Huang SQ, Chen ZX, Lv CS, Wen L. Amelioration of olfactory dysfunction in a mouse model of Parkinson's disease via enhancing GABAergic signaling. Cell Biosci 2023; 13:101. [PMID: 37270503 DOI: 10.1186/s13578-023-01049-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/06/2023] [Indexed: 06/05/2023] Open
Abstract
BACKGROUND Olfactory dysfunction is among the earliest non-motor symptoms of Parkinson's disease (PD). As the foremost pathological hallmark, α-synuclein initiates the pathology in the olfactory pathway at the early stage of PD, particularly in the olfactory epithelium (OE) and olfactory bulb (OB). However, the local neural microcircuit mechanisms underlying olfactory dysfunction between OE and OB in early PD remain unknown. RESULTS We observed that odor detection and discrimination were impaired in 6-month-old SNCA-A53T mice, while their motor ability remained unaffected. It was confirmed that α-synuclein increased and accumulated in OB but not in OE. Notably, the hyperactivity of mitral/tufted cells and the excitation/inhibition imbalance in OB were found in 6-month-old SNCA-A53T mice, which was attributed to the impaired GABAergic transmission and aberrant expression of GABA transporter 1 and vesicular GABA transporter in OB. We further showed that tiagabine, a potent and selective GABA reuptake inhibitor, could reverse the impaired olfactory function and GABAergic signaling in OB of SNCA-A53T mice. CONCLUSIONS Taken together, our findings demonstrate potential synaptic mechanisms of local neural microcircuit underlying olfactory dysfunction at the early stage of PD. These results highlight the critical role of aberrant GABAergic signaling of OB in early diagnosis and provide a potential therapeutic strategy for early-stage PD.
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Affiliation(s)
- Xing-Yang Liu
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Ke Wang
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Xian-Hua Deng
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Yi-Hua Wei
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Rui Guo
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Sui-Feng Liu
- Zhongshan Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361100, China
| | - Yi-Fan Zhu
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Jia-Jun Zhong
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Jing-Yuan Zheng
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Meng-Dan Wang
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Qiu-Hong Ye
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Jian-Quan He
- Zhongshan Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361100, China
| | - Kai-Hang Guo
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Jun-Rong Zhu
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Shu-Qiong Huang
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Ze-Xu Chen
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Chong-Shan Lv
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China
| | - Lei Wen
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, Fujian, 361102, China.
- Xiamen Key Laboratory for TCM Dampness Disease, Neurology & Immunology Research, Department of Traditional Chinese Medicine, Longyan Hospital of Traditional Chinese Medicine, School of Medicine, Xiamen University, Longyan, Fujian, 364000, China.
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12
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Wang S, Li X. A revisit of the amygdala theory of autism: Twenty years after. Neuropsychologia 2023; 183:108519. [PMID: 36803966 PMCID: PMC10824605 DOI: 10.1016/j.neuropsychologia.2023.108519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 01/23/2023] [Accepted: 02/16/2023] [Indexed: 02/19/2023]
Abstract
The human amygdala has long been implicated to play a key role in autism spectrum disorder (ASD). Yet it remains unclear to what extent the amygdala accounts for the social dysfunctions in ASD. Here, we review studies that investigate the relationship between amygdala function and ASD. We focus on studies that employ the same task and stimuli to directly compare people with ASD and patients with focal amygdala lesions, and we also discuss functional data associated with these studies. We show that the amygdala can only account for a limited number of deficits in ASD (primarily face perception tasks but not social attention tasks), a network view is, therefore, more appropriate. We next discuss atypical brain connectivity in ASD, factors that can explain such atypical brain connectivity, and novel tools to analyze brain connectivity. Lastly, we discuss new opportunities from multimodal neuroimaging with data fusion and human single-neuron recordings that can enable us to better understand the neural underpinnings of social dysfunctions in ASD. Together, the influential amygdala theory of autism should be extended with emerging data-driven scientific discoveries such as machine learning-based surrogate models to a broader framework that considers brain connectivity at the global scale.
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Affiliation(s)
- Shuo Wang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
| | - Xin Li
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
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13
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Hollestein V, Poelmans G, Forde NJ, Beckmann CF, Ecker C, Mann C, Schäfer T, Moessnang C, Baumeister S, Banaschewski T, Bourgeron T, Loth E, Dell'Acqua F, Murphy DGM, Puts NA, Tillmann J, Charman T, Jones EJH, Mason L, Ambrosino S, Holt R, Bölte S, Buitelaar JK, Naaijen J. Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure. Transl Psychiatry 2023; 13:18. [PMID: 36681677 PMCID: PMC9867712 DOI: 10.1038/s41398-023-02317-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/22/2023] Open
Abstract
The excitatory/inhibitory (E/I) imbalance hypothesis posits that imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism. However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. We used innovative analysis methods-combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT) to investigate relationships between genetic variance, brain structure and autism symptomatology of participants from the AIMS-2-TRIALS LEAP cohort (autism = 359, male/female = 258/101; neurotypical control participants = 279, male/female = 178/101) aged 6-30 years. Using competitive gene-set analyses, we investigated whether aggregated genetic variation in glutamate and GABA gene-sets could be associated with behavioral measures of autism symptoms and brain structural variation. Further, using the same gene-sets, we corelated expression profiles throughout the cortex with differences in CT between autistic and neurotypical control participants, as well as in separate sensory subgroups. The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group. In adolescents and adults, brain regions with greater gene-expression of glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants although in opposing directions. Additionally, the gene expression profiles were associated with CT profiles in separate sensory subgroups. Our results suggest complex relationships between E/I related genetics and autism symptom profiles as well as brain structure alterations, where there may be differential roles for glutamate and GABA.
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Affiliation(s)
- Viola Hollestein
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Geert Poelmans
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Natalie J Forde
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christine Ecker
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Caroline Mann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Tim Schäfer
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | - Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Sarah Baumeister
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tobias Banaschewski
- Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Thomas Bourgeron
- Institut Pasteur, Human Genetics and Cognitive Functions Unit, Paris, France
| | - Eva Loth
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Flavio Dell'Acqua
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council (MRC) Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Nicolaas A Puts
- Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council (MRC) Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Julian Tillmann
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, London, UK
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Henry Wellcome Building, London, UK
| | - Sara Ambrosino
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Rosemary Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, Western Australia
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
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14
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Barkdoll K, Lu Y, Barranca VJ. New insights into binocular rivalry from the reconstruction of evolving percepts using model network dynamics. Front Comput Neurosci 2023; 17:1137015. [PMID: 37034441 PMCID: PMC10079880 DOI: 10.3389/fncom.2023.1137015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/07/2023] [Indexed: 04/11/2023] Open
Abstract
When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.
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15
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Eichmüller OL, Knoblich JA. Human cerebral organoids - a new tool for clinical neurology research. Nat Rev Neurol 2022; 18:661-680. [PMID: 36253568 PMCID: PMC9576133 DOI: 10.1038/s41582-022-00723-9] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/07/2022] [Indexed: 11/21/2022]
Abstract
The current understanding of neurological diseases is derived mostly from direct analysis of patients and from animal models of disease. However, most patient studies do not capture the earliest stages of disease development and offer limited opportunities for experimental intervention, so rarely yield complete mechanistic insights. The use of animal models relies on evolutionary conservation of pathways involved in disease and is limited by an inability to recreate human-specific processes. In vitro models that are derived from human pluripotent stem cells cultured in 3D have emerged as a new model system that could bridge the gap between patient studies and animal models. In this Review, we summarize how such organoid models can complement classical approaches to accelerate neurological research. We describe our current understanding of neurodevelopment and how this process differs between humans and other animals, making human-derived models of disease essential. We discuss different methodologies for producing organoids and how organoids can be and have been used to model neurological disorders, including microcephaly, Zika virus infection, Alzheimer disease and other neurodegenerative disorders, and neurodevelopmental diseases, such as Timothy syndrome, Angelman syndrome and tuberous sclerosis. We also discuss the current limitations of organoid models and outline how organoids can be used to revolutionize research into the human brain and neurological diseases.
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Affiliation(s)
- Oliver L Eichmüller
- IMBA-Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
- University of Heidelberg, Heidelberg, Germany
| | - Juergen A Knoblich
- IMBA-Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria.
- Medical University of Vienna, Department of Neurology, Vienna, Austria.
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16
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Noel JP, Paredes R, Terrebonne E, Feldman JI, Woynaroski T, Cascio CJ, Seriès P, Wallace MT. Inflexible Updating of the Self-Other Divide During a Social Context in Autism: Psychophysical, Electrophysiological, and Neural Network Modeling Evidence. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:756-764. [PMID: 33845169 PMCID: PMC8521572 DOI: 10.1016/j.bpsc.2021.03.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 03/08/2021] [Accepted: 03/29/2021] [Indexed: 01/21/2023]
Abstract
BACKGROUND Autism spectrum disorder (ASD) affects many aspects of life, from social interactions to (multi)sensory processing. Similarly, the condition expresses at a variety of levels of description, from genetics to neural circuits and interpersonal behavior. We attempt to bridge between domains and levels of description by detailing the behavioral, electrophysiological, and putative neural network basis of peripersonal space (PPS) updating in ASD during a social context, given that the encoding of this space relies on appropriate multisensory integration, is malleable by social context, and is thought to delineate the boundary between the self and others. METHODS Fifty (20 male/30 female) young adults, either diagnosed with ASD or age- and sex-matched individuals, took part in a visuotactile reaction time task indexing PPS, while high-density electroencephalography was continuously recorded. Neural network modeling was performed in silico. RESULTS Multisensory psychophysics demonstrates that while PPS in neurotypical individuals shrinks in the presence of others-as to "give space"-this does not occur in ASD. Likewise, electroencephalography recordings suggest that multisensory integration is altered by social context in neurotypical individuals but not in individuals with ASD. Finally, a biologically plausible neural network model shows, as a proof of principle, that PPS updating may be inflexible in ASD owing to the altered excitatory/inhibitory balance that characterizes neural circuits in animal models of ASD. CONCLUSIONS Findings are conceptually in line with recent statistical inference accounts, suggesting diminished flexibility in ASD, and further these observations by suggesting within an example relevant for social cognition that such inflexibility may be due to excitatory/inhibitory imbalances.
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Affiliation(s)
- Jean-Paul Noel
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Center for Neural Science, New York University, New York, New York.
| | - Renato Paredes
- Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom
| | - Emily Terrebonne
- Undergraduate Neuroscience Program, Vanderbilt University, Nashville, Tennessee; School of Medicine and Health Sciences, George Washington University, Washington, District of Columbia
| | - Jacob I Feldman
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Tiffany Woynaroski
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Carissa J Cascio
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Peggy Seriès
- Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark T Wallace
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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17
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Abstract
Autism is a neurodevelopmental disorder of unknown etiology. Recently, there has been a growing interest in sensory processing in autism as a core phenotype. However, basic questions remain unanswered. Here, we review the major findings and models of perception in autism and point to methodological issues that have led to conflicting results. We show that popular models of perception in autism, such as the reduced prior hypothesis, cannot explain the many and varied findings. To resolve these issues, we point to the benefits of using rigorous psychophysical methods to study perception in autism. We advocate for perceptual models that provide a detailed explanation of behavior while also taking into account factors such as context, learning, and attention. Furthermore, we demonstrate the importance of tracking changes over the course of development to reveal the causal pathways and compensatory mechanisms. Finally, we propose a developmental perceptual narrowing account of the condition. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Bat-Sheva Hadad
- Department of Special Education and The Edmond J. Safra Brain Research Center, University of Haifa, Haifa, Israel; ,
| | - Amit Yashar
- Department of Special Education and The Edmond J. Safra Brain Research Center, University of Haifa, Haifa, Israel; ,
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18
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Park S, Zikopoulos B, Yazdanbakhsh A. Visual illusion susceptibility in autism: A neural model. Eur J Neurosci 2022; 56:4246-4265. [PMID: 35701859 PMCID: PMC9541695 DOI: 10.1111/ejn.15739] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 04/04/2022] [Accepted: 06/06/2022] [Indexed: 11/26/2022]
Abstract
While atypical sensory perception is reported among individuals with autism spectrum disorder (ASD), the underlying neural mechanisms of autism that give rise to disruptions in sensory perception remain unclear. We developed a neural model with key physiological, functional and neuroanatomical parameters to investigate mechanisms underlying the range of representations of visual illusions related to orientation perception in typically developed subjects compared to individuals with ASD. Our results showed that two theorized autistic traits, excitation/inhibition imbalance and weakening of top‐down modulation, could be potential candidates for reduced susceptibility to some visual illusions. Parametric correlation between cortical suppression, balance of excitation/inhibition, feedback from higher visual areas on one hand and susceptibility to a class of visual illusions related to orientation perception on the other hand provide the opportunity to investigate the contribution and complex interactions of distinct sensory processing mechanisms in ASD. The novel approach used in this study can be used to link behavioural, functional and neuropathological studies; estimate and predict perceptual and cognitive heterogeneity in ASD; and form a basis for the development of novel diagnostics and therapeutics.
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Affiliation(s)
- Sangwook Park
- Computational Neuroscience and Vision Laboratory, Boston University, Boston, Massachusetts, USA
| | - Basilis Zikopoulos
- Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA.,Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA.,Graduate Program for Neuroscience, Boston University, Boston, Massachusetts, USA
| | - Arash Yazdanbakhsh
- Computational Neuroscience and Vision Laboratory, Boston University, Boston, Massachusetts, USA.,Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA.,Graduate Program for Neuroscience, Boston University, Boston, Massachusetts, USA.,Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
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19
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Haigh SM, Brosseau P, Eack SM, Leitman DI, Salisbury DF, Behrmann M. Hyper-Sensitivity to Pitch and Poorer Prosody Processing in Adults With Autism: An ERP Study. Front Psychiatry 2022; 13:844830. [PMID: 35693971 PMCID: PMC9174755 DOI: 10.3389/fpsyt.2022.844830] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/20/2022] [Indexed: 01/30/2023] Open
Abstract
Individuals with autism typically experience a range of symptoms, including abnormal sensory sensitivities. However, there are conflicting reports on the sensory profiles that characterize the sensory experience in autism that often depend on the type of stimulus. Here, we examine early auditory processing to simple changes in pitch and later auditory processing of more complex emotional utterances. We measured electroencephalography in 24 adults with autism and 28 controls. First, tones (1046.5Hz/C6, 1108.7Hz/C#6, or 1244.5Hz/D#6) were repeated three times or nine times before the pitch changed. Second, utterances of delight or frustration were repeated three or six times before the emotion changed. In response to the simple pitched tones, the autism group exhibited larger mismatch negativity (MMN) after nine standards compared to controls and produced greater trial-to-trial variability (TTV). In response to the prosodic utterances, the autism group showed smaller P3 responses when delight changed to frustration compared to controls. There was no significant correlation between ERPs to pitch and ERPs to prosody. Together, this suggests that early auditory processing is hyper-sensitive in autism whereas later processing of prosodic information is hypo-sensitive. The impact the different sensory profiles have on perceptual experience in autism may be key to identifying behavioral treatments to reduce symptoms.
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Affiliation(s)
- Sarah M. Haigh
- Department of Psychology and Institute for Neuroscience, University of Nevada, Reno, NV, United States
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Pat Brosseau
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Shaun M. Eack
- School of Social Work, University of Pittsburgh, Pittsburgh, PA, United States
| | - David I. Leitman
- Division of Translational Research, National Institute of Mental Health, Bethesda, MD, United States
| | - Dean F. Salisbury
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Marlene Behrmann
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
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20
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Noel JP, Shivkumar S, Dokka K, Haefner RM, Angelaki DE. Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder. eLife 2022; 11:71866. [PMID: 35579424 PMCID: PMC9170250 DOI: 10.7554/elife.71866] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 05/15/2022] [Indexed: 12/02/2022] Open
Abstract
Autism spectrum disorder (ASD) is characterized by a panoply of social, communicative, and sensory anomalies. As such, a central goal of computational psychiatry is to ascribe the heterogenous phenotypes observed in ASD to a limited set of canonical computations that may have gone awry in the disorder. Here, we posit causal inference - the process of inferring a causal structure linking sensory signals to hidden world causes - as one such computation. We show that audio-visual integration is intact in ASD and in line with optimal models of cue combination, yet multisensory behavior is anomalous in ASD because this group operates under an internal model favoring integration (vs. segregation). Paradoxically, during explicit reports of common cause across spatial or temporal disparities, individuals with ASD were less and not more likely to report common cause, particularly at small cue disparities. Formal model fitting revealed differences in both the prior probability for common cause (p-common) and choice biases, which are dissociable in implicit but not explicit causal inference tasks. Together, this pattern of results suggests (i) different internal models in attributing world causes to sensory signals in ASD relative to neurotypical individuals given identical sensory cues, and (ii) the presence of an explicit compensatory mechanism in ASD, with these individuals putatively having learned to compensate for their bias to integrate in explicit reports.
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Affiliation(s)
- Jean-Paul Noel
- Center for Neural Science, New York University, New York City, United States
| | | | - Kalpana Dokka
- Department of Neuroscience, Baylor College of Medicine, Houston, United States
| | - Ralf M Haefner
- Brain and Cognitive Sciences, University of Rochester, Rochester, United States
| | - Dora E Angelaki
- Center for Neural Science, New York University, New York City, United States.,Department of Neuroscience, Baylor College of Medicine, Houston, United States
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21
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Tortelli C, Pomè A, Turi M, Igliozzi R, Burr DC, Binda P. Contextual Information Modulates Pupil Size in Autistic Children. Front Neurosci 2022; 16:752871. [PMID: 35431787 PMCID: PMC9011183 DOI: 10.3389/fnins.2022.752871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 02/24/2022] [Indexed: 11/13/2022] Open
Abstract
Recent Bayesian models suggest that perception is more “data-driven” and less dependent on contextual information in autistic individuals than others. However, experimental tests of this hypothesis have given mixed results, possibly due to the lack of objectivity of the self-report methods typically employed. Here we introduce an objective no-report paradigm based on pupillometry to assess the processing of contextual information in autistic children, together with a comparison clinical group. After validating in neurotypical adults a child-friendly pupillometric paradigm, in which we embedded test images within an animation movie that participants watched passively, we compared pupillary response to images of the sun and meaningless control images in children with autism vs. age- and IQ-matched children presenting developmental disorders unrelated to the autistic spectrum. Both clinical groups showed stronger pupillary constriction for the sun images compared with control images, like the neurotypical adults. However, there was no detectable difference between autistic children and the comparison group, despite a significant difference in pupillary light responses, which were enhanced in the autistic group. Our report introduces an objective technique for studying perception in clinical samples and children. The lack of statistically significant group differences in our tests suggests that autistic children and the comparison group do not show large differences in perception of these stimuli. This opens the way to further studies testing contextual processing at other levels of perception.
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Affiliation(s)
- Chiara Tortelli
- Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Pisa, Italy
| | - Antonella Pomè
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Firenze, Firenze, Italy
| | - Marco Turi
- Fondazione Stella Maris Mediterraneo, Matera, Italy
| | | | - David C. Burr
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Firenze, Firenze, Italy
| | - Paola Binda
- Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
- *Correspondence: Paola Binda,
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22
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Echeveste R, Ferrante E, Milone DH, Samengo I. Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference. Netw Neurosci 2022; 6:196-212. [PMID: 36605888 PMCID: PMC9810278 DOI: 10.1162/netn_a_00219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/01/2021] [Indexed: 01/09/2023] Open
Abstract
Theories for autism spectrum disorder (ASD) have been formulated at different levels, ranging from physiological observations to perceptual and behavioral descriptions. Understanding the physiological underpinnings of perceptual traits in ASD remains a significant challenge in the field. Here we show how a recurrent neural circuit model that was optimized to perform sampling-based inference and displays characteristic features of cortical dynamics can help bridge this gap. The model was able to establish a mechanistic link between two descriptive levels for ASD: a physiological level, in terms of inhibitory dysfunction, neural variability, and oscillations, and a perceptual level, in terms of hypopriors in Bayesian computations. We took two parallel paths-inducing hypopriors in the probabilistic model, and an inhibitory dysfunction in the network model-which lead to consistent results in terms of the represented posteriors, providing support for the view that both descriptions might constitute two sides of the same coin.
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Affiliation(s)
- Rodrigo Echeveste
- Research Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, Argentina,* Corresponding Author:
| | - Enzo Ferrante
- Research Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, Argentina
| | - Diego H. Milone
- Research Institute for Signals, Systems, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, Argentina
| | - Inés Samengo
- Medical Physics Department and Balseiro Institute (CNEA-UNCUYO/CONICET), Bariloche, Argentina
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23
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Chen F, Liu W, Liu P, Wang Z, Zhou Y, Liu X, Li A. α-Synuclein aggregation in the olfactory bulb induces olfactory deficits by perturbing granule cells and granular-mitral synaptic transmission. NPJ Parkinsons Dis 2021; 7:114. [PMID: 34903719 PMCID: PMC8668919 DOI: 10.1038/s41531-021-00259-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 11/21/2021] [Indexed: 11/10/2022] Open
Abstract
Olfactory dysfunction is an early pre-motor symptom of Parkinson's disease (PD) but the neural mechanisms underlying this dysfunction remain largely unknown. Aggregation of α-synuclein is observed in the olfactory bulb (OB) during the early stages of PD, indicating a relationship between α-synuclein pathology and hyposmia. Here we investigate whether and how α-synuclein aggregates modulate neural activity in the OB at the single-cell and synaptic levels. We induced α-synuclein aggregation specifically in the OB via overexpression of double-mutant human α-synuclein by an adeno-associated viral (AAV) vector. We found that α-synuclein aggregation in the OB decreased the ability of mice to detect odors and to perceive attractive odors. The spontaneous activity and odor-evoked firing rates of single mitral/tufted cells (M/Ts) were increased by α-synuclein aggregates with the amplitude of odor-evoked high-gamma oscillations increased. Furthermore, the decreased activity in granule cells (GCs) and impaired inhibitory synaptic function were responsible for the observed hyperactivity of M/Ts induced by α-synuclein aggregates. These results provide direct evidences of the role of α-synuclein aggregates on PD-related olfactory dysfunction and reveal the neural circuit mechanisms by which olfaction is modulated by α-synuclein pathology.
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Affiliation(s)
- Fengjiao Chen
- grid.417303.20000 0000 9927 0537Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China
| | - Wei Liu
- grid.417303.20000 0000 9927 0537Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China
| | - Penglai Liu
- grid.417303.20000 0000 9927 0537Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China
| | - Zhen Wang
- grid.417303.20000 0000 9927 0537School of Life Science, Xuzhou Medical University, Xuzhou, China
| | - You Zhou
- grid.417303.20000 0000 9927 0537School of Life Science, Xuzhou Medical University, Xuzhou, China
| | - Xingyu Liu
- grid.417303.20000 0000 9927 0537School of Life Science, Xuzhou Medical University, Xuzhou, China
| | - Anan Li
- Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China.
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24
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Divisive normalization unifies disparate response signatures throughout the human visual hierarchy. Proc Natl Acad Sci U S A 2021; 118:2108713118. [PMID: 34772812 PMCID: PMC8609633 DOI: 10.1073/pnas.2108713118] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/30/2021] [Indexed: 01/04/2023] Open
Abstract
A canonical neural computation is a mathematical operation applied by the brain in a wide variety of contexts and capable of explaining and unifying seemingly unrelated neural and perceptual phenomena. Here, we use a combination of state-of-the-art experiments (ultra-high-field functional MRI) and mathematical methods (population receptive field [pRF] modeling) to uniquely demonstrate the role of divisive normalization (DN) as the canonical neural computation underlying visuospatial responses throughout the human visual hierarchy. The DN pRF model provides a tool to investigate and interpret the computational processes underlying neural responses in human and animal recordings, but also in clinical and cognitive dimensions. Neural processing is hypothesized to apply the same mathematical operations in a variety of contexts, implementing so-called canonical neural computations. Divisive normalization (DN) is considered a prime candidate for a canonical computation. Here, we propose a population receptive field (pRF) model based on DN and evaluate it using ultra-high-field functional MRI (fMRI). The DN model parsimoniously captures seemingly disparate response signatures with a single computation, superseding existing pRF models in both performance and biological plausibility. We observe systematic variations in specific DN model parameters across the visual hierarchy and show how they relate to differences in response modulation and visuospatial information integration. The DN model delivers a unifying framework for visuospatial responses throughout the human visual hierarchy and provides insights into its underlying information-encoding computations. These findings extend the role of DN as a canonical computation to neuronal populations throughout the human visual hierarchy.
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25
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Eye Direction Detection and Perception as Premises of a Social Brain: A Narrative Review of Behavioral and Neural Data. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2021; 22:1-20. [PMID: 34642895 DOI: 10.3758/s13415-021-00959-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/23/2021] [Indexed: 11/08/2022]
Abstract
The eyes and the gaze are important stimuli for social interaction in humans. Impaired recognition of facial identity, facial emotions, and inference of the intentions of others may result from difficulties in extracting information relevant to the eye region, mainly the direction of gaze. Therefore, a review of these data is of interest. Behavioral data demonstrating the importance of the eye region and how humans respond to gaze direction are reviewed narratively, and several theoretical models on how visual information on gaze is processed are discussed to propose a unified hypothesis. Several issues that have not yet been investigated are identified. The authors tentatively suggest experiments that might help progress research in this area. The neural aspects are subsequently reviewed to best describe the low-level and higher-level visual information processing stages in the targeted subcortical and cortical areas. A specific neural network is proposed on the basis of the literature. Various gray areas, such as the temporality of the processing of visual information, the question of salience priority, and the coordination between the two hemispheres, remain unclear and require further investigations. Finally, disordered gaze direction detection mechanisms and their consequences on social cognition and behavior are discussed as key deficiencies in several conditions, such as autism spectrum disorder, 22q11.2 deletion, schizophrenia, and social anxiety disorder. This narrative review provides significant additional data showing that the detection and perception of someone's gaze is an essential part of the development of our social brain.
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26
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Sapey-Triomphe LA, Temmerman J, Puts NAJ, Wagemans J. Prediction learning in adults with autism and its molecular correlates. Mol Autism 2021; 12:64. [PMID: 34615532 PMCID: PMC8493731 DOI: 10.1186/s13229-021-00470-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/23/2021] [Indexed: 12/28/2022] Open
Abstract
Background According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. Methods Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). Results Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. Limitations We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. Conclusions Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-021-00470-6.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium. .,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium.
| | - Joke Temmerman
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences and the Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, King's College London, London, SE5 8AF, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE5 8AF, UK
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium
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27
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Abstract
We measured the pupil response to a light stimulus subject to a size illusion and found that stimuli perceived as larger evoke a stronger pupillary response. The size illusion depends on combining retinal signals with contextual 3D information; contextual processing is thought to vary across individuals, being weaker in individuals with stronger autistic traits. Consistent with this theory, autistic traits correlated negatively with the magnitude of pupil modulations in our sample of neurotypical adults; however, psychophysical measurements of the illusion did not correlate with autistic traits, or with the pupil modulations. This shows that pupillometry provides an accurate objective index of complex perceptual processes, particularly useful for quantifying interindividual differences, and potentially more informative than standard psychophysical measures.
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28
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Noel JP, Zhang LQ, Stocker AA, Angelaki DE. Individuals with autism spectrum disorder have altered visual encoding capacity. PLoS Biol 2021; 19:e3001215. [PMID: 33979326 PMCID: PMC8143398 DOI: 10.1371/journal.pbio.3001215] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 05/24/2021] [Accepted: 04/01/2021] [Indexed: 11/24/2022] Open
Abstract
Perceptual anomalies in individuals with autism spectrum disorder (ASD) have been attributed to an imbalance in weighting incoming sensory evidence with prior knowledge when interpreting sensory information. Here, we show that sensory encoding and how it adapts to changing stimulus statistics during feedback also characteristically differs between neurotypical and ASD groups. In a visual orientation estimation task, we extracted the accuracy of sensory encoding from psychophysical data by using an information theoretic measure. Initially, sensory representations in both groups reflected the statistics of visual orientations in natural scenes, but encoding capacity was overall lower in the ASD group. Exposure to an artificial (i.e., uniform) distribution of visual orientations coupled with performance feedback altered the sensory representations of the neurotypical group toward the novel experimental statistics, while also increasing their total encoding capacity. In contrast, neither total encoding capacity nor its allocation significantly changed in the ASD group. Across both groups, the degree of adaptation was correlated with participants’ initial encoding capacity. These findings highlight substantial deficits in sensory encoding—independent from and potentially in addition to deficits in decoding—in individuals with ASD. It is increasingly recognized that individuals with Autism Spectrum Disorder (ASD) show anomalies in perception, and these have been recently attributed to altered decoding (i.e. interpretation of sensory signals). This study reveals that independent of these changes, individuals with ASD show upstream deficits in sensory encoding (i.e., how samples are drawn from the environment).
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Affiliation(s)
- Jean-Paul Noel
- Center for Neural Science, New York University, New York City, New York, United States of America
| | - Ling-Qi Zhang
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Alan A. Stocker
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Dora E. Angelaki
- Center for Neural Science, New York University, New York City, New York, United States of America
- * E-mail:
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29
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Mariscal MG, Berry-Kravis E, Buxbaum JD, Ethridge LE, Filip-Dhima R, Foss-Feig JH, Kolevzon A, Modi ME, Mosconi MW, Nelson CA, Powell CM, Siper PM, Soorya L, Thaliath A, Thurm A, Zhang B, Sahin M, Levin AR. Shifted phase of EEG cross-frequency coupling in individuals with Phelan-McDermid syndrome. Mol Autism 2021; 12:29. [PMID: 33910615 PMCID: PMC8082621 DOI: 10.1186/s13229-020-00411-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 12/28/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Phelan-McDermid Syndrome (PMS) is a rare condition caused by deletion or mutation of the SHANK3 gene. Individuals with PMS frequently present with intellectual disability, autism spectrum disorder, and other neurodevelopmental challenges. Electroencephalography (EEG) can provide a window into network-level function in PMS. METHODS Here, we analyze EEG data collected across multiple sites in individuals with PMS (n = 26) and typically developing individuals (n = 15). We quantify oscillatory power, alpha-gamma phase-amplitude coupling strength, and phase bias, a measure of the phase of cross frequency coupling thought to reflect the balance of feedforward (bottom-up) and feedback (top-down) activity. RESULTS We find individuals with PMS display increased alpha-gamma phase bias (U = 3.841, p < 0.0005), predominantly over posterior electrodes. Most individuals with PMS demonstrate positive overall phase bias while most typically developing individuals demonstrate negative overall phase bias. Among individuals with PMS, strength of alpha-gamma phase-amplitude coupling was associated with Sameness, Ritualistic, and Compulsive behaviors as measured by the Repetitive Behavior Scales-Revised (Beta = 0.545, p = 0.011). CONCLUSIONS Increased phase bias suggests potential circuit-level mechanisms underlying phenotype in PMS, offering opportunities for back-translation of findings into animal models and targeting in clinical trials.
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Affiliation(s)
| | - Elizabeth Berry-Kravis
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
- Department of Biochemistry, Rush University Medical Center, Chicago, IL, USA
| | - Joseph D Buxbaum
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, NY, USA
- Department of Neuroscience, Mount Sinai School of Medicine, New York, NY, USA
| | - Lauren E Ethridge
- Department of Pediatrics, University of Oklahoma Health Science Center, Oklahoma City, OK, USA
| | - Rajna Filip-Dhima
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Jennifer H Foss-Feig
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
| | - Alexander Kolevzon
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Meera E Modi
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Matthew W Mosconi
- Clinical Child Psychology Program, Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, KS, USA
| | - Charles A Nelson
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
| | - Craig M Powell
- Department of Neurobiology, UAB School of Medicine, Birmingham, AL, USA
| | - Paige M Siper
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
| | - Latha Soorya
- Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA
| | - Andrew Thaliath
- Department of Pediatrics, Rush University Medical Center, Chicago, IL, USA
| | - Audrey Thurm
- Intramural Research Program, National Institute of Mental Health, Bethesda, USA
| | - Bo Zhang
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - April R Levin
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
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30
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Jassim N, Baron-Cohen S, Suckling J. Meta-analytic evidence of differential prefrontal and early sensory cortex activity during non-social sensory perception in autism. Neurosci Biobehav Rev 2021; 127:146-157. [PMID: 33887326 DOI: 10.1016/j.neubiorev.2021.04.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 03/26/2021] [Accepted: 04/12/2021] [Indexed: 01/24/2023]
Abstract
To date, neuroimaging research has had a limited focus on non-social features of autism. As a result, neurobiological explanations for atypical sensory perception in autism are lacking. To address this, we quantitively condensed findings from the non-social autism fMRI literature in line with the current best practices for neuroimaging meta-analyses. Using activation likelihood estimation (ALE), we conducted a series of robust meta-analyses across 83 experiments from 52 fMRI studies investigating differences between autistic (n = 891) and typical (n = 967) participants. We found that typical controls, compared to autistic people, show greater activity in the prefrontal cortex (BA9, BA10) during perception tasks. More refined analyses revealed that, when compared to typical controls, autistic people show greater recruitment of the extrastriate V2 cortex (BA18) during visual processing. Taken together, these findings contribute to our understanding of current theories of autistic perception, and highlight some of the challenges of cognitive neuroscience research in autism.
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Affiliation(s)
- Nazia Jassim
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom.
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom
| | - John Suckling
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom; Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Forvie Site, Robinson Way, Cambridge, CB2 0SZ, United Kingdom
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31
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Komatsu H, Watanabe E, Fukuchi M. Psychiatric Neural Networks and Precision Therapeutics by Machine Learning. Biomedicines 2021; 9:403. [PMID: 33917863 PMCID: PMC8068267 DOI: 10.3390/biomedicines9040403] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/28/2021] [Accepted: 04/06/2021] [Indexed: 12/12/2022] Open
Abstract
Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.
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Affiliation(s)
- Hidetoshi Komatsu
- Medical Affairs, Kyowa Pharmaceutical Industry Co., Ltd., Osaka 530-0005, Japan
- Department of Biological Science, Graduate School of Science, Nagoya University, Nagoya City 464-8602, Japan
| | - Emi Watanabe
- Interactive Group, Accenture Japan Ltd., Tokyo 108-0073, Japan;
| | - Mamoru Fukuchi
- Laboratory of Molecular Neuroscience, Faculty of Pharmacy, Takasaki University of Health and Welfare, Gunma 370-0033, Japan;
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32
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Van de Cruys S, Lemmens L, Sapey-Triomphe LA, Chetverikov A, Noens I, Wagemans J. Structural and contextual priors affect visual search in children with and without autism. Autism Res 2021; 14:1484-1495. [PMID: 33811474 DOI: 10.1002/aur.2511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/15/2021] [Accepted: 03/22/2021] [Indexed: 11/07/2022]
Abstract
Bayesian predictive coding theories of autism spectrum disorder propose that impaired acquisition or a broader shape of prior probability distributions lies at the core of the condition. However, we still know very little about how probability distributions are learned and encoded by children, let alone children with autism. Here, we take advantage of a recently developed distribution learning paradigm to characterize how children with and without autism acquire information about probability distributions. Twenty-four autistic and 25-matched neurotypical children searched for an odd-one-out target among a set of distractor lines with orientations sampled from a Gaussian distribution repeated across multiple trials to allow for learning of the parameters (mean and variance) of the distribution. We could measure the width (variance) of the participant's encoded distribution by introducing a target-distractor role-reversal while varying the similarity between target and previous distractor mean. Both groups performed similarly on the visual search task and learned the distractor distribution to a similar extent. However, the variance learned was much broader than the one presented, consistent with less informative priors in children irrespective of autism diagnosis. These findings have important implications for Bayesian accounts of perception throughout development, and Bayesian accounts of autism specifically. LAY SUMMARY: Recent theories about the underlying cognitive mechanisms of autism propose that the way autistic individuals estimate variability or uncertainty in their perceptual environment may differ from how typical individuals do so. Children had to search an oddly tilted line in a set of lines pointing in different directions, and based on their response times we examined how they learned about the variability in a set of objects. We found that autistic children learn variability as well as typical children, but both groups learn with less precision than typical adults do on the same task.
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Affiliation(s)
- Sander Van de Cruys
- Laboratory of Experimental Psychology, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Lisa Lemmens
- Laboratory of Experimental Psychology, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Laurie-Anne Sapey-Triomphe
- Laboratory of Experimental Psychology, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Andrey Chetverikov
- Visual Computation Lab, Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Ilse Noens
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Johan Wagemans
- Laboratory of Experimental Psychology, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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33
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Norcia AM, Lee A, Meredith WJ, Kohler PJ, Pei F, Ghassan SA, Libove RA, Phillips JM, Hardan AY. A case-control study of visual, auditory and audio-visual sensory interactions in children with autism spectrum disorder. J Vis 2021; 21:5. [PMID: 33830169 PMCID: PMC8039569 DOI: 10.1167/jov.21.4.5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 11/09/2020] [Indexed: 01/23/2023] Open
Abstract
To assess the relative integrity of early visual and auditory processes in autism spectrum disorder (ASD), we used frequency-tagged visual and auditory stimulation and high-density electroencephalogram recordings of unimodal and dual-modality responses in a case-control design. To test for the specificity of effects on ASD, we recorded from a smaller group of children with attention-deficit hyperactivity disorder (ADHD). Horizontal 3 cycle per degree (cpd) gratings were presented at 5 Hz, and a random stream of /ba/, /da/, /ga/ syllables was presented at 6 Hz. Grating contrast response functions were measured unimodally and in the presence of a 64-dB auditory input. Auditory response functions were measured unimodally and in the presence of a 40% contrast grating. Children with ASD (n = 34) and ADHD (n = 13) showed a common lack of audio-visual interaction compared to typically developing children (n = 40) when measured at the first harmonic of the visual stimulus frequency. Both patient groups also showed depressed first harmonic responses at low contrast, but the ADHD group had consistently higher first-harmonic responses at high contrast. Children with ASD had a preferential loss of second-harmonic (transient) responses. The alteredtransient responses in ASD are likely to arise very early in the visual pathway and could thus have downstream consequences for many other visual mechanisms and processes. The alteration in audio-visual interaction could be a signature of a comorbid phenotype shared by ASD and ADHD, possibly due to alterations in attentional selection systems.
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Affiliation(s)
- Anthony M Norcia
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Azalea Lee
- Department of Psychology, Stanford University, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | | | - Peter J Kohler
- Department of Psychology, York University, Toronto, ON, Canada
- Centre for Vision Research, York University, Toronto, ON, Canada
| | - Francesca Pei
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Stephanie A Ghassan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Robin A Libove
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Jennifer M Phillips
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Antonio Y Hardan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
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34
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Finnemann JJS, Plaisted-Grant K, Moore J, Teufel C, Fletcher PC. Low-level, prediction-based sensory and motor processes are unimpaired in Autism. Neuropsychologia 2021; 156:107835. [PMID: 33794277 DOI: 10.1016/j.neuropsychologia.2021.107835] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 03/09/2021] [Accepted: 03/19/2021] [Indexed: 01/08/2023]
Abstract
A new promising account of human brain function suggests that sensory cortices try to optimise information processing via predictions that are based on prior experiences. The brain is thus likened to a probabilistic prediction machine. There has been a growing - though inconsistent - literature to suggest that features of autism spectrum conditions (ASCs) are associated with a deficit in modelling the world through such prediction-based inference. However empirical evidence for differences in low-level sensorimotor predictions in autism is still lacking. One approach to examining predictive processing in the sensorimotor domain is in the context of self-generated (predictable) as opposed to externally-generated (less predictable) effects. We employed two complementary tasks - forcematching and intentional binding - which examine self-versus externally-generated action effects in terms of sensory attenuation and intentional binding respectively in adults with and without autism. The results show that autism was associated with normal levels of sensory attenuation of internally-generated force and with unaltered temporal attraction of voluntary actions and their outcomes. Thus, our results do not support a general deficit in predictive processing in autism.
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Affiliation(s)
- Johanna J S Finnemann
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, United Kingdom.
| | - Kate Plaisted-Grant
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom
| | - James Moore
- Department of Psychology, Goldsmiths, University of London, London, SE14 6NW, United Kingdom
| | - Christoph Teufel
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, United Kingdom
| | - Paul C Fletcher
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, CB21 5EF, United Kingdom; Wellcome Trust MRC Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
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35
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Idei H, Murata S, Yamashita Y, Ogata T. Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder. Neural Netw 2021; 138:150-163. [PMID: 33652371 DOI: 10.1016/j.neunet.2021.01.033] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 12/19/2020] [Accepted: 01/29/2021] [Indexed: 10/22/2022]
Abstract
Neurodevelopmental disorders are characterized by heterogeneous and non-specific nature of their clinical symptoms. In particular, hyper- and hypo-reactivity to sensory stimuli are diagnostic features of autism spectrum disorder and are reported across many neurodevelopmental disorders. However, computational mechanisms underlying the unusual paradoxical behaviors remain unclear. In this study, using a robot controlled by a hierarchical recurrent neural network model with predictive processing and learning mechanism, we simulated how functional disconnection altered the learning process and subsequent behavioral reactivity to environmental change. The results show that, through the learning process, long-range functional disconnection between distinct network levels could simultaneously lower the precision of sensory information and higher-level prediction. The alteration caused a robot to exhibit sensory-dominated and sensory-ignoring behaviors ascribed to sensory hyper- and hypo-reactivity, respectively. As long-range functional disconnection became more severe, a frequency shift from hyporeactivity to hyperreactivity was observed, paralleling an early sign of autism spectrum disorder. Furthermore, local functional disconnection at the level of sensory processing similarly induced hyporeactivity due to low sensory precision. These findings suggest a computational explanation for paradoxical sensory behaviors in neurodevelopmental disorders, such as coexisting hyper- and hypo-reactivity to sensory stimulus. A neurorobotics approach may be useful for bridging various levels of understanding in neurodevelopmental disorders and providing insights into mechanisms underlying complex clinical symptoms.
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Affiliation(s)
- Hayato Idei
- Department of Intermedia Studies, Waseda University, Tokyo, 169-8555, Japan.
| | - Shingo Murata
- Department of Electronics and Electrical Engineering, Keio University, Kanagawa, 223-8522, Japan.
| | - Yuichi Yamashita
- Department of Information Medicine, National Center of Neurology and Psychiatry, Tokyo, 187-8502, Japan.
| | - Tetsuya Ogata
- Department of Intermedia Art and Science, Waseda University, Tokyo, 169-8555, Japan.
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36
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Sensory over-responsivity is related to GABAergic inhibition in thalamocortical circuits. Transl Psychiatry 2021; 11:39. [PMID: 33436538 PMCID: PMC7804323 DOI: 10.1038/s41398-020-01154-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 11/17/2020] [Accepted: 11/30/2020] [Indexed: 12/13/2022] Open
Abstract
Sensory over-responsivity (SOR), extreme sensitivity to or avoidance of sensory stimuli (e.g., scratchy fabrics, loud sounds), is a highly prevalent and impairing feature of neurodevelopmental disorders such as autism spectrum disorders (ASD), anxiety, and ADHD. Previous studies have found overactive brain responses and reduced modulation of thalamocortical connectivity in response to mildly aversive sensory stimulation in ASD. These findings suggest altered thalamic sensory gating which could be associated with an excitatory/inhibitory neurochemical imbalance, but such thalamic neurochemistry has never been examined in relation to SOR. Here we utilized magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to examine the relationship between thalamic and somatosensory cortex inhibitory (gamma-aminobutyric acid, GABA) and excitatory (glutamate) neurochemicals with the intrinsic functional connectivity of those regions in 35 ASD and 35 typically developing pediatric subjects. Although there were no diagnostic group differences in neurochemical concentrations in either region, within the ASD group, SOR severity correlated negatively with thalamic GABA (r = -0.48, p < 0.05) and positively with somatosensory glutamate (r = 0.68, p < 0.01). Further, in the ASD group, thalamic GABA concentration predicted altered connectivity with regions previously implicated in SOR. These variations in GABA and associated network connectivity in the ASD group highlight the potential role of GABA as a mechanism underlying individual differences in SOR, a major source of phenotypic heterogeneity in ASD. In ASD, abnormalities of the thalamic neurochemical balance could interfere with the thalamic role in integrating, relaying, and inhibiting attention to sensory information. These results have implications for future research and GABA-modulating pharmacologic interventions.
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37
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Huys QJM, Browning M, Paulus MP, Frank MJ. Advances in the computational understanding of mental illness. Neuropsychopharmacology 2021; 46:3-19. [PMID: 32620005 PMCID: PMC7688938 DOI: 10.1038/s41386-020-0746-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/11/2020] [Accepted: 06/15/2020] [Indexed: 12/11/2022]
Abstract
Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. It encompasses both data-driven and theory-driven efforts. Here, recent advances in theory-driven work are reviewed. We argue that the brain is a computational organ. As such, an understanding of the illnesses arising from it will require a computational framework. The review divides work up into three theoretical approaches that have deep mathematical connections: dynamical systems, Bayesian inference and reinforcement learning. We discuss both general and specific challenges for the field, and suggest ways forward.
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Affiliation(s)
- Quentin J M Huys
- Division of Psychiatry and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Camden and Islington NHS Trust, London, UK.
| | - Michael Browning
- Computational Psychiatry Lab, Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Health NHS Trust, Oxford, UK
| | - Martin P Paulus
- Laureate Institute For Brain Research (LIBR), Tulsa, OK, USA
| | - Michael J Frank
- Cognitive, Linguistic & Psychological Sciences, Neuroscience Graduate Program, Brown University, Providence, RI, USA
- Carney Center for Computational Brain Science, Carney Institute for Brain Science Psychiatry and Human Behavior, Brown University, Providence, RI, USA
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38
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Reduction of higher-order occipital GABA and impaired visual perception in acute major depressive disorder. Mol Psychiatry 2021; 26:6747-6755. [PMID: 33863994 PMCID: PMC8760062 DOI: 10.1038/s41380-021-01090-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 03/16/2021] [Accepted: 03/29/2021] [Indexed: 11/08/2022]
Abstract
Major depressive disorder (MDD) is a complex state-dependent psychiatric illness for which biomarkers linking psychophysical, biochemical, and psychopathological changes remain yet elusive, though. Earlier studies demonstrate reduced GABA in lower-order occipital cortex in acute MDD leaving open its validity and significance for higher-order visual perception, though. The goal of our study is to fill that gap by combining psychophysical investigation of visual perception with measurement of GABA concentration in middle temporal visual area (hMT+) in acute depressed MDD. Psychophysically, we observe a highly specific deficit in visual surround motion suppression in a large sample of acute MDD subjects which, importantly, correlates with symptom severity. Both visual deficit and its relation to symptom severity are replicated in the smaller MDD sample that received MRS. Using high-field 7T proton Magnetic resonance spectroscopy (1H-MRS), acute MDD subjects exhibit decreased GABA concentration in visual MT+ which, unlike in healthy subjects, no longer correlates with their visual motion performance, i.e., impaired SI. In sum, our combined psychophysical-biochemical study demonstrates an important role of reduced occipital GABA for altered visual perception and psychopathological symptoms in acute MDD. Bridging the gap from the biochemical level of occipital GABA over visual-perceptual changes to psychopathological symptoms, our findings point to the importance of the occipital cortex in acute depressed MDD including its role as candidate biomarker.
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39
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Mercado E, Chow K, Church BA, Lopata C. Perceptual category learning in autism spectrum disorder: Truth and consequences. Neurosci Biobehav Rev 2020; 118:689-703. [PMID: 32910926 PMCID: PMC7744437 DOI: 10.1016/j.neubiorev.2020.08.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 08/01/2020] [Accepted: 08/29/2020] [Indexed: 02/01/2023]
Abstract
The ability to categorize is fundamental to cognitive development. Some categories emerge effortlessly and rapidly while others can take years of experience to acquire. Children with autism spectrum disorder (ASD) are often able to name and sort objects, suggesting that their categorization abilities are largely intact. However, recent experimental work shows that the categories formed by individuals with ASD may diverge substantially from those that most people learn. This review considers how atypical perceptual category learning can affect cognitive development in children with ASD and how atypical categorization may contribute to many of the socially problematic symptoms associated with this disorder. Theoretical approaches to understanding perceptual processing and category learning at both the behavioral and neural levels are assessed in relation to known alterations in perceptual category learning associated with ASD. Mismatches between the ways in which children learn to organize perceived events relative to their peers and adults can accumulate over time, leading to difficulties in communication, social interactions, academic performance, and behavioral flexibility.
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Affiliation(s)
- Eduardo Mercado
- University at Buffalo, The State University of New York, Dept. of Psychology, Buffalo, NY, 14260, USA.
| | - Karen Chow
- University at Buffalo, The State University of New York, Dept. of Psychology, Buffalo, NY, 14260, USA
| | - Barbara A Church
- Georgia State University, Language Research Center, 3401 Panthersville Rd., Decatur, GA, 30034, USA
| | - Christopher Lopata
- Canisius College, Institute for Autism Research, Science Hall, 2001 Main St., Buffalo, NY, 14208, USA
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40
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Steel A, Mikkelsen M, Edden RAE, Robertson CE. Regional balance between glutamate+glutamine and GABA+ in the resting human brain. Neuroimage 2020; 220:117112. [PMID: 32619710 PMCID: PMC9652611 DOI: 10.1016/j.neuroimage.2020.117112] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 06/17/2020] [Accepted: 06/27/2020] [Indexed: 12/04/2022] Open
Abstract
Models of healthy brain function and psychiatric conditions assume that excitatory and inhibitory activity are balanced in the human brain at multiple spatial and temporal scales. In human neuroimaging, concentrations of the major excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters are measured in vivo using magnetic resonance spectroscopy (MRS). However, despite the central importance of E/I balance to theories of brain function, a relationship between regional glutamate and GABA levels in the human brain has not been shown. We addressed this question in a large corpus of edited MRS data collected at 19 different sites (n = 220). Consistent with the notion of E/I balance, we found that levels of glutamate+glutamine (Glx) and GABA+ were highly correlated (R = 0.52, p = 2.86 x 10−14). This relationship held when controlling for site, scanner vendor, and demographics. Controlling for neurochemicals associated with neuronal density and metabolism (i.e. N-acetylaspartate and creatine) significantly reduced the correlation between GABA+ and Glx, suggesting that the levels of GABA+ and Glx may be critically linked to regional metabolism. These results are consistent with the notion that excitation and inhibition are balanced in the human brain.
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Affiliation(s)
- Adam Steel
- Department of Psychology and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Caroline E Robertson
- Department of Psychology and Brain Sciences, Dartmouth College, Hanover, NH, USA
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41
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Abstract
Abnormal sensory processing has been observed in autism, including superior visual motion discrimination, but the neural basis for these sensory changes remains unknown. Leveraging well-characterized suppressive neural circuits in the visual system, we used behavioral and fMRI tasks to demonstrate a significant reduction in neural suppression in young adults with autism spectrum disorder (ASD) compared to neurotypical controls. MR spectroscopy measurements revealed no group differences in neurotransmitter signals. We show how a computational model that incorporates divisive normalization, as well as narrower top-down gain (that could result, for example, from a narrower window of attention), can explain our observations and divergent previous findings. Thus, weaker neural suppression is reflected in visual task performance and fMRI measures in ASD, and may be attributable to differences in top-down processing. Sensory hypersensitivity is common in autism spectrum disorders. Using functional MRI, psychophysics, and computational modeling, Schallmo et al. show that differences in visual motion perception in ASD are accompanied by weaker neural suppression in visual cortex.
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42
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Increased variability but intact integration during visual navigation in Autism Spectrum Disorder. Proc Natl Acad Sci U S A 2020; 117:11158-11166. [PMID: 32358192 DOI: 10.1073/pnas.2000216117] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects' dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants' beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.
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43
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Uncharacteristic Task-Evoked Pupillary Responses Implicate Atypical Locus Ceruleus Activity in Autism. J Neurosci 2020; 40:3815-3826. [PMID: 32253362 DOI: 10.1523/jneurosci.2680-19.2020] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/07/2020] [Accepted: 02/29/2020] [Indexed: 02/03/2023] Open
Abstract
Autism spectrum disorder (ASD) is characterized partly by atypical attentional engagement, reflected in exaggerated and variable responses to sensory stimuli. Attentional engagement is known to be regulated by the locus ceruleus (LC). Moderate baseline LC activity globally dampens neural responsivity and is associated with adaptive deployment and narrowing of attention to task-relevant stimuli. In contrast, increased baseline LC activity enhances neural responsivity across cortex and widening of attention to environmental stimuli regardless of their task relevance. Given attentional atypicalities in ASD, this study is the first to evaluate whether, under different attentional task demands, individuals with ASD exhibit a different profile of LC activity compared with typically developing controls. Males and females with ASD and age- and gender-matched controls participated in a one-back letter detection test while task-evoked pupillary responses, an established correlate for LC activity, were recorded. Participants completed this task in two conditions, either in the absence or presence of distractor auditory tones. Compared with controls, individuals with ASD evinced atypical pupillary responses in the presence versus absence of distractors. Notably, this atypical pupillary profile was evident despite the fact that both groups exhibited equivalent task performance. Moreover, between-group differences in pupillary responses were observed specifically in response to task-relevant events, providing confirmation that the group differences most likely were specifically associated with distinctions in LC activity. These findings suggest that individuals with ASD show atypical modulation of LC activity with changes in attentional demands, offering a possible mechanistic and neurobiological account for attentional atypicalities in ASD.SIGNIFICANCE STATEMENT Individuals with autism spectrum disorder (ASD) exhibit atypical attentional behaviors, including altered sensory responses and atypical fixedness, but the neural mechanism underlying these behaviors remains elusive. One candidate mechanism is atypical locus ceruleus (LC) activity, as the LC plays a critical role in attentional modulation. Specifically, LC activity is involved in regulating the trade-off between environmental exploration and focused attention. This study shows that, under tightly controlled conditions, task-evoked pupil responses, an LC activity proxy, are lower in individuals with ASD than in controls, but only in the presence of task-irrelevant stimuli. This suggests that individuals with ASD evince atypical modulation of LC activity in accordance with changes in attentional demands, offering a mechanistic account for attentional atypicalities in ASD.
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44
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Pomè A, Binda P, Cicchini GM, Burr DC. Pupillometry correlates of visual priming, and their dependency on autistic traits. J Vis 2020; 20:3. [DOI: 10.1167/jovi.20.3.3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Affiliation(s)
- Antonella Pomè
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy
| | - Paola Binda
- Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
- Institute of Neuroscience, National Research Council, Pisa, Italy
| | | | - David C. Burr
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy
- Institute of Neuroscience, National Research Council, Pisa, Italy
- School of Psychology, University of Sydney, Sydney, Australia
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45
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Pomè A, Binda P, Cicchini GM, Burr DC. Pupillometry correlates of visual priming, and their dependency on autistic traits. J Vis 2020; 20:3. [PMID: 32181859 PMCID: PMC7405690 DOI: 10.1167/jov.20.3.3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
In paradigms of visual search where the search feature (say color) can change from trial to trials, responses are faster for trials where the search color is repeated than when it changes. This is a clear example of "priming" of attention. Here we test whether the priming effects can be revealed by pupillometry, and also whether they are related to autistic-like personality traits, as measured by the Autism-Spectrum Quotient (AQ). We repeated Maljkovic and Nakayama's (1994) classic priming experiment, asking subjects to identify rapidly the shape of a singleton target defined by color. As expected, reaction times were faster when target color repeated, and the effect accumulated over several trials; but the magnitude of the effect did not correlate with AQ. Reaction times were also faster when target position was repeated, again independent of AQ. Presentation of stimuli caused the pupil to dilate, and the magnitude of dilation was greater for switched than repeated trials. This effect did not accumulate over trials, and did not correlate with the reaction times difference, suggesting that the two indexes measure independent aspects of the priming phenomenon. Importantly, the amplitude of pupil modulation correlated negatively with AQ, and was significant only for those participants with low AQ. The results confirm that pupillometry can track perceptual and attentional processes, and furnish useful information unobtainable from standard psychophysics, including interesting dependencies on personality traits.
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Affiliation(s)
- Antonella Pomè
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy
| | - Paola Binda
- Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy,Institute of Neuroscience, National Research Council, Pisa, Italy
| | | | - David C. Burr
- Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy,Institute of Neuroscience, National Research Council, Pisa, Italy,School of Psychology, University of Sydney, Sydney, Australia
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46
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Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, Jones EJH, Jones RM, Pickles A, State MW, Taylor JL, Veenstra-VanderWeele J. Autism spectrum disorder. Nat Rev Dis Primers 2020; 6:5. [PMID: 31949163 PMCID: PMC8900942 DOI: 10.1038/s41572-019-0138-4] [Citation(s) in RCA: 632] [Impact Index Per Article: 158.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/26/2019] [Indexed: 12/27/2022]
Abstract
Autism spectrum disorder is a construct used to describe individuals with a specific combination of impairments in social communication and repetitive behaviours, highly restricted interests and/or sensory behaviours beginning early in life. The worldwide prevalence of autism is just under 1%, but estimates are higher in high-income countries. Although gross brain pathology is not characteristic of autism, subtle anatomical and functional differences have been observed in post-mortem, neuroimaging and electrophysiological studies. Initially, it was hoped that accurate measurement of behavioural phenotypes would lead to specific genetic subtypes, but genetic findings have mainly applied to heterogeneous groups that are not specific to autism. Psychosocial interventions in children can improve specific behaviours, such as joint attention, language and social engagement, that may affect further development and could reduce symptom severity. However, further research is necessary to identify the long-term needs of people with autism, and treatments and the mechanisms behind them that could result in improved independence and quality of life over time. Families are often the major source of support for people with autism throughout much of life and need to be considered, along with the perspectives of autistic individuals, in both research and practice.
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Affiliation(s)
- Catherine Lord
- Departments of Psychiatry and School of Education, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Traolach S Brugha
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Tony Charman
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | | | - Guillaume Dumas
- Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | | | - Emily J H Jones
- Centre for Brain & Cognitive Development, University of London, London, UK
| | - Rebecca M Jones
- The Sackler Institute for Developmental Psychobiology, New York, NY, USA
- The Center for Autism and the Developing Brain, White Plains, NY, USA
| | - Andrew Pickles
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Matthew W State
- Department of Psychiatry, Langley Porter Psychiatric Institute and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Julie Lounds Taylor
- Department of Pediatrics and Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA
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Divisively Normalized Integration of Multisensory Error Information Develops Motor Memories Specific to Vision and Proprioception. J Neurosci 2020; 40:1560-1570. [PMID: 31924610 DOI: 10.1523/jneurosci.1745-19.2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 11/17/2019] [Accepted: 12/13/2019] [Indexed: 11/21/2022] Open
Abstract
Both visual and proprioceptive information contribute to the accuracy of limb movement, but the mechanism of integration of these different modality signals for movement control and learning remains controversial. We aimed to elucidate the mechanism of multisensory integration for motor adaptation by evaluating single-trial adaptation (i.e., aftereffect) induced by visual and proprioceptive perturbations while male and female human participants performed reaching movements. The force-channel method was used to precisely impose several combinations of visual and proprioceptive perturbations (i.e., error), including an instance when the directions of perturbation in both stimuli opposed each another. In the subsequent probe force-channel trial, the lateral force against the channel was quantified as the aftereffect to clarify the mechanism by which the motor adaptation system corrects movement in the event of visual and proprioceptive errors. We observed that the aftereffects had complex dependence on the visual and proprioceptive errors. Although this pattern could not be explained by previously proposed computational models based on the reliability of sensory information, we found that it could be reasonably explained by a mechanism known as divisive normalization, which was the reported mechanism underlying the integration of multisensory signals in neurons. Furthermore, we discovered evidence that the motor memory for each sensory modality developed separately in accordance with a divisive normalization mechanism and that the outputs of both memories were integrated. These results provide a novel view of the utilization and integration of different sensory modality signals in motor adaptation.SIGNIFICANCE STATEMENT The mechanism of utilization of multimodal sensory information by the motor control system to perform limb movements with accuracy is a fundamental question. However, the mechanism of integration of these different sensory modalities for movement control and learning remains highly debatable. Herein, we demonstrate that multisensory integration in the motor learning system can be reasonably explained by divisive normalization, a canonical computation, ubiquitously observed in the brain (Carandini and Heeger, 2011). Moreover, we provide evidence of a novel idea that integration does not occur at the sensory information processing level, but at the motor execution level, after the motor memory for each sensory modality is separately created.
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Optimized but Not Maximized Cue Integration for 3D Visual Perception. eNeuro 2020; 7:ENEURO.0411-19.2019. [PMID: 31836597 PMCID: PMC6948924 DOI: 10.1523/eneuro.0411-19.2019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 12/05/2019] [Accepted: 12/08/2019] [Indexed: 02/02/2023] Open
Abstract
Reconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear whether this is true for non-human primates (NHPs). Here, we assessed 3D perception in macaque monkeys using a planar surface orientation discrimination task. Perception was accurate across a wide range of spatial poses (orientations and distances), but precision was highly dependent on the plane's pose. The monkeys achieved robust 3D perception by dynamically reweighting the integration of stereoscopic and perspective cues according to their pose-dependent reliabilities. Errors in performance could be explained by a prior resembling the 3D orientation statistics of natural scenes. We used neural network simulations based on 3D orientation-selective neurons recorded from the same monkeys to assess how neural computation might constrain perception. The perceptual data were consistent with a model in which the responses of two independent neuronal populations representing stereoscopic cues and perspective cues (with perspective signals from the two eyes combined using nonlinear canonical computations) were optimally integrated through linear summation. Perception of combined-cue stimuli was optimal given this architecture. However, an alternative architecture in which stereoscopic cues, left eye perspective cues, and right eye perspective cues were represented by three independent populations yielded two times greater precision than the monkeys. This result suggests that, due to canonical computations, cue integration for 3D perception is optimized but not maximized.
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Idei H, Murata S, Yamashita Y, Ogata T. Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder. Front Psychiatry 2020; 11:762. [PMID: 32903328 PMCID: PMC7434834 DOI: 10.3389/fpsyt.2020.00762] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/17/2020] [Indexed: 11/13/2022] Open
Abstract
Neurodevelopmental disorders, including autism spectrum disorder, have been intensively investigated at the neural, cognitive, and behavioral levels, but the accumulated knowledge remains fragmented. In particular, developmental learning aspects of symptoms and interactions with the physical environment remain largely unexplored in computational modeling studies, although a leading computational theory has posited associations between psychiatric symptoms and an unusual estimation of information uncertainty (precision), which is an essential aspect of the real world and is estimated through learning processes. Here, we propose a mechanistic explanation that unifies the disparate observations via a hierarchical predictive coding and developmental learning framework, which is demonstrated in experiments using a neural network-controlled robot. The results show that, through the developmental learning process, homogeneous intrinsic neuronal excitability at the neural level induced via self-organization changes at the information processing level, such as hyper sensory precision and overfitting to sensory noise. These changes led to multifaceted alterations at the behavioral level, such as inflexibility, reduced generalization, and motor clumsiness. In addition, these behavioral alterations were accompanied by fluctuating neural activity and excessive development of synaptic connections. These findings might bridge various levels of understandings in autism spectrum and other neurodevelopmental disorders and provide insights into the disease processes underlying observed behaviors and brain activities in individual patients. This study shows the potential of neurorobotics frameworks for modeling how psychiatric disorders arise from dynamic interactions among the brain, body, and uncertain environments.
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Affiliation(s)
- Hayato Idei
- Department of Intermedia Studies, Waseda University, Tokyo, Japan
| | - Shingo Murata
- Principles of Informatics Research Division, National Institute of Informatics, Tokyo, Japan
| | - Yuichi Yamashita
- Department of Information Medicine, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Tetsuya Ogata
- Department of Intermedia Art and Science, Waseda University, Tokyo, Japan
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Mohl JT, Caruso VC, Tokdar ST, Groh JM. Sensitivity and specificity of a Bayesian single trial analysis for time varying neural signals. NEURONS, BEHAVIOR, DATA ANALYSIS AND THEORY 2020; 3:https://nbdt.scholasticahq.com/article/11880-sensitivity-and-specificity-of-a-bayesian-single-trial-analysis-for-time-varying-neural-signals. [PMID: 34505116 PMCID: PMC8425354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
We recently reported the existence of fluctuations in neural signals that may permit neurons to code multiple simultaneous stimuli sequentially across time [1]. This required deploying a novel statistical approach to permit investigation of neural activity at the scale of individual trials. Here we present tests using synthetic data to assess the sensitivity and specificity of this analysis. We fabricated datasets to match each of several potential response patterns derived from single-stimulus response distributions. In particular, we simulated dual stimulus trial spike counts that reflected fluctuating mixtures of the single stimulus spike counts, stable intermediate averages, single stimulus winner-take-all, or response distributions that were outside the range defined by the single stimulus responses (such as summation or suppression). We then assessed how well the analysis recovered the correct response pattern as a function of the number of simulated trials and the difference between the simulated responses to each "stimulus" alone. We found excellent recovery of the mixture, intermediate, and outside categories (>97% correct), and good recovery of the single/winner-take-all category (>90% correct) when the number of trials was >20 and the single-stimulus response rates were 50Hz and 20Hz respectively. Both larger numbers of trials and greater separation between the single stimulus firing rates improved categorization accuracy. These results provide a benchmark, and guidelines for data collection, for use of this method to investigate coding of multiple items at the individual-trial time scale.
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Affiliation(s)
- Jeff T. Mohl
- Duke Institute for Brain Sciences, Duke University, Durham, NC, 27708, USA,Center for Cognitive Neuroscience, Duke University,Department of Neurobiology, Duke University
| | - Valeria C. Caruso
- Duke Institute for Brain Sciences, Duke University, Durham, NC, 27708, USA,Center for Cognitive Neuroscience, Duke University,Department of Neurobiology, Duke University,Department of Psychology and Neuroscience, Duke University,Center for Human Growth and Development, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Surya T. Tokdar
- Duke Institute for Brain Sciences, Duke University, Durham, NC, 27708, USA,Department of Statistical Science, Duke University
| | - Jennifer M. Groh
- Duke Institute for Brain Sciences, Duke University, Durham, NC, 27708, USA,Center for Cognitive Neuroscience, Duke University,Department of Neurobiology, Duke University,Department of Psychology and Neuroscience, Duke University
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