Pub Date : 2024-08-12DOI: 10.1101/2024.08.12.607531
Meimei Guo, Feiyang Zhang, Sha Liu, Yi Zhang, Lesheng Wang, Jian Song, Wei Wei, Xiang Li
Acute sleep deprivation (ASD) negatively impacts fear memory, but the underlying mechanisms are not fully understood. Transient receptor potential vanilloid 4 (TRPV4), a cation channel which is closely correlated with the concentration of Ca2+, and neuronal Ca2+ overloading is a crucial inducement of learning and memory impairment. This study utilized an acute sleep-deprived mouse model combined with fear conditioning to investigate these mechanisms. mRNA sequencing revealed increased expression of TRPV4 in mice with ASD-induced fear memory impairment. Notably, knockdown of TRPV4 reversed ASD-induced fear memory impairment. ASD leads to the increased concentration of Ca2+. Additionally, we observed a reduction in spine density and a significant decrease in postsynaptic density protein 95 (PSD95), which is associated with synaptic plasticity, in sleep-deprived fear memory impairment mice. This indicates that ASD may cause overloaded Ca2+, disrupting synaptic plasticity and impairing fear memory. Moreover, TRPV4 knockdown significantly decreased Ca2+ concentration, mitigated the loss of dendritic spines and reduction of PSD95, contributing to the restoration of fear memory. These findings indicate a potential protective role of TRPV4 knockdown in counteracting ASD-induced fear memory deficits. Collectively, our results highlight that TRPV4 may be a potential therapeutic target in mediating fear memory impairment due to ASD and underscore the importance of sleep management for conditions like PTSD.
{"title":"The role of TRPV4 in acute sleep deprivation-induced fear memory impairment","authors":"Meimei Guo, Feiyang Zhang, Sha Liu, Yi Zhang, Lesheng Wang, Jian Song, Wei Wei, Xiang Li","doi":"10.1101/2024.08.12.607531","DOIUrl":"https://doi.org/10.1101/2024.08.12.607531","url":null,"abstract":"Acute sleep deprivation (ASD) negatively impacts fear memory, but the underlying mechanisms are not fully understood. Transient receptor potential vanilloid 4 (TRPV4), a cation channel which is closely correlated with the concentration of Ca2+, and neuronal Ca2+ overloading is a crucial inducement of learning and memory impairment. This study utilized an acute sleep-deprived mouse model combined with fear conditioning to investigate these mechanisms. mRNA sequencing revealed increased expression of TRPV4 in mice with ASD-induced fear memory impairment. Notably, knockdown of TRPV4 reversed ASD-induced fear memory impairment. ASD leads to the increased concentration of Ca2+. Additionally, we observed a reduction in spine density and a significant decrease in postsynaptic density protein 95 (PSD95), which is associated with synaptic plasticity, in sleep-deprived fear memory impairment mice. This indicates that ASD may cause overloaded Ca2+, disrupting synaptic plasticity and impairing fear memory. Moreover, TRPV4 knockdown significantly decreased Ca2+ concentration, mitigated the loss of dendritic spines and reduction of PSD95, contributing to the restoration of fear memory. These findings indicate a potential protective role of TRPV4 knockdown in counteracting ASD-induced fear memory deficits. Collectively, our results highlight that TRPV4 may be a potential therapeutic target in mediating fear memory impairment due to ASD and underscore the importance of sleep management for conditions like PTSD.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-12DOI: 10.1101/2024.08.11.607263
Matthew J Mender, Ayobami L Ward, Luis H Cubillos, Madison M Kelberman, Joseph T Costello, Hisham Temmar, Dylan M Wallace, Edanjen T Lin, Jordan L W Lam, Matthew S Willsey, Nishant Ganesh Kumar, Theodore A Kung, Parag G Patil, Cynthia A Chestek
Brain-machine interface (BMI) controlled functional electrical stimulation (FES) is a promising treatment to restore hand movements to people with cervical spinal cord injury. Recent intracortical BMIs have shown unprecedented successes in decoding user intentions, however the hand movements restored by FES have largely been limited to predetermined grasps. Restoring dexterous hand movements will require continuous control of many biomechanically linked degrees-of-freedom in the hand, such as wrist and finger flexion, that would form the basis of those movements. Here we investigate the ability to restore simultaneous wrist and finger flexion, which would enable grasping with a controlled hand posture and assist in manipulating objects once grasped. We demonstrate that intramuscular FES can enable monkeys with temporarily paralyzed hands to move their fingers and wrist across a functional range of motion, spanning an average 88.6 degrees at the metacarpophalangeal joint flexion and 71.3 degrees of wrist flexion, and intramuscular FES can control both joints simultaneously in a real-time task. Additionally, we demonstrate a monkey using an intracortical BMI to control the wrist and finger flexion in a virtual hand, both before and after the hand is temporarily paralyzed, even achieving success rates and acquisition times equivalent to able-bodied control with BMI control after temporary paralysis in two sessions. Together, this outlines a method using an artificial brain-to-body interface that could restore continuous wrist and finger movements after spinal cord injury.
{"title":"Functional Electrical Stimulation and Brain-Machine Interfaces for Simultaneous Control of Wrist and Finger Flexion","authors":"Matthew J Mender, Ayobami L Ward, Luis H Cubillos, Madison M Kelberman, Joseph T Costello, Hisham Temmar, Dylan M Wallace, Edanjen T Lin, Jordan L W Lam, Matthew S Willsey, Nishant Ganesh Kumar, Theodore A Kung, Parag G Patil, Cynthia A Chestek","doi":"10.1101/2024.08.11.607263","DOIUrl":"https://doi.org/10.1101/2024.08.11.607263","url":null,"abstract":"Brain-machine interface (BMI) controlled functional electrical stimulation (FES) is a promising treatment to restore hand movements to people with cervical spinal cord injury. Recent intracortical BMIs have shown unprecedented successes in decoding user intentions, however the hand movements restored by FES have largely been limited to predetermined grasps. Restoring dexterous hand movements will require continuous control of many biomechanically linked degrees-of-freedom in the hand, such as wrist and finger flexion, that would form the basis of those movements. Here we investigate the ability to restore simultaneous wrist and finger flexion, which would enable grasping with a controlled hand posture and assist in manipulating objects once grasped. We demonstrate that intramuscular FES can enable monkeys with temporarily paralyzed hands to move their fingers and wrist across a functional range of motion, spanning an average 88.6 degrees at the metacarpophalangeal joint flexion and 71.3 degrees of wrist flexion, and intramuscular FES can control both joints simultaneously in a real-time task. Additionally, we demonstrate a monkey using an intracortical BMI to control the wrist and finger flexion in a virtual hand, both before and after the hand is temporarily paralyzed, even achieving success rates and acquisition times equivalent to able-bodied control with BMI control after temporary paralysis in two sessions. Together, this outlines a method using an artificial brain-to-body interface that could restore continuous wrist and finger movements after spinal cord injury.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integral role of the insula cortex in sensory and cognitive function has been well documented in humans, and fine anatomical details characterising the insula have been extensively investigated ex-vivo in both human and non-human primates. However, in-vivo studies of insula anatomy in humans (in general), and within-insula parcellation (in particular) have been limited. The current study leverages 7 tesla magnetic resonance imaging to delineate T1-weighted intensity profiles within the human cortex, serving as an indirect proxy of myelination. Our analysis revealed two separate clusters of relatively high and low T1-weighted signal intensity across the insula cortex located in three distinct cortical locations within the posterior, anterior, and middle insula. The posterior and anterior cortical locations are characterised by elevated T1-weighted signal intensities, contrasting with lower intensity observed in the middle insular cortical location, compatible with ex-vivo studies. Importantly, the detection of the high T1-weighted anterior cluster is determined by the choice of brain atlas employed to define the insular ROI. We obtain reliable in-vivo within-insula parcellation at the individual and group levels, across two separate cohorts acquired in two separate sites (n1 = 21, Glasgow, UK; n2 = 101, Amsterdam, NL). These results reflect new insights into the insula anatomical structure, in-vivo, while highlighting the use of 7 tesla in neuroimaging. Specifically, the current study also paves the way to study within-insula parcellation at 7 tesla and above, and discusses further implications for individualised medicine approaches.
{"title":"Delineating In-Vivo T1-Weighted Intensity Profiles Within the Human Insula Cortex Using 7-Tesla MRI","authors":"Connor Dalby, Austin Jon Dibble, Joana Carvalheiro, Filippo Queirazza, Michele Sevegnani, Monika Harvey, Michele Svanera, Alessio Fracasso","doi":"10.1101/2024.08.05.605123","DOIUrl":"https://doi.org/10.1101/2024.08.05.605123","url":null,"abstract":"The integral role of the insula cortex in sensory and cognitive function has been well documented in humans, and fine anatomical details characterising the insula have been extensively investigated ex-vivo in both human and non-human primates. However, in-vivo studies of insula anatomy in humans (in general), and within-insula parcellation (in particular) have been limited. The current study leverages 7 tesla magnetic resonance imaging to delineate T1-weighted intensity profiles within the human cortex, serving as an indirect proxy of myelination. Our analysis revealed two separate clusters of relatively high and low T1-weighted signal intensity across the insula cortex located in three distinct cortical locations within the posterior, anterior, and middle insula. The posterior and anterior cortical locations are characterised by elevated T1-weighted signal intensities, contrasting with lower intensity observed in the middle insular cortical location, compatible with ex-vivo studies. Importantly, the detection of the high T1-weighted anterior cluster is determined by the choice of brain atlas employed to define the insular ROI. We obtain reliable in-vivo within-insula parcellation at the individual and group levels, across two separate cohorts acquired in two separate sites (n1 = 21, Glasgow, UK; n2 = 101, Amsterdam, NL). These results reflect new insights into the insula anatomical structure, in-vivo, while highlighting the use of 7 tesla in neuroimaging. Specifically, the current study also paves the way to study within-insula parcellation at 7 tesla and above, and discusses further implications for individualised medicine approaches.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-12DOI: 10.1101/2024.08.11.607514
Alejandro Luarte, Javiera Gallardo, Daniela Corvalan, Ankush Chakraborty, Claudio Gouveia-Roque, Francisca Bertin, Carlos Contreras, Juan Pablo Ramirez, Andre Weber, Waldo Acevedo, Werner Zuschratter, Rodrigo Herrera, Ursula Wyneken, Andrea Paula Lima, Tatiana Adasme, Antonia Figueroa, Carolina Gonzalez, Christian Gonzalez-Billault, Ulrich Hengst, Andres Couve
The regenerative potential of developing cortical axons following injury depends on intrinsic mechanisms, such as axon-autonomous protein synthesis, that are still not fully understood. An emerging factor in this regenerative process is the bi-directional interplay between microtubule dynamics and structural proteins of the axonal endoplasmic reticulum. Therefore, we hypothesize that locally synthesized structural proteins of the endoplasmic reticulum may regulate microtubule dynamics and the outgrowth of injured cortical axons. This hypothesis is supported by RNA data-mining, which identified Reticulon-1 as the sole ER-shaping protein consistently present in axonal transcriptomes and found it to be downregulated following cortical axon injury. Using compartmentalized microfluidic chambers, we demonstrate that local knockdown of Reticulon-1 mRNA enhances outgrowth while reducing the distal tubulin levels of injured cortical axons. Additionally, live cell imaging shows injury-induced reductions in microtubule growth rate and length, which are fully restored by axonal Reticulon-1 knockdown. Interestingly, axonal inhibition of the microtubule-severing protein Spastin fully prevents the effects of local Reticulon-1 knockdown on outgrowth and tubulin levels, while not affecting microtubule dynamics. Furthermore, we provide evidence supporting that the Reticulon-1C isoform is locally synthesized in injured axons and associates with Spastin to inhibit its severing activity. Our findings reveal a novel injury-dependent mechanism in which a locally synthesized ER-shaping protein lessens microtubule dynamics and the outgrowth of cortical axons.
{"title":"Local Synthesis of Reticulon-1C Lessens the Outgrowth of Injured Axons by Controlling Spastin Activity","authors":"Alejandro Luarte, Javiera Gallardo, Daniela Corvalan, Ankush Chakraborty, Claudio Gouveia-Roque, Francisca Bertin, Carlos Contreras, Juan Pablo Ramirez, Andre Weber, Waldo Acevedo, Werner Zuschratter, Rodrigo Herrera, Ursula Wyneken, Andrea Paula Lima, Tatiana Adasme, Antonia Figueroa, Carolina Gonzalez, Christian Gonzalez-Billault, Ulrich Hengst, Andres Couve","doi":"10.1101/2024.08.11.607514","DOIUrl":"https://doi.org/10.1101/2024.08.11.607514","url":null,"abstract":"The regenerative potential of developing cortical axons following injury depends on intrinsic mechanisms, such as axon-autonomous protein synthesis, that are still not fully understood. An emerging factor in this regenerative process is the bi-directional interplay between microtubule dynamics and structural proteins of the axonal endoplasmic reticulum. Therefore, we hypothesize that locally synthesized structural proteins of the endoplasmic reticulum may regulate microtubule dynamics and the outgrowth of injured cortical axons. This hypothesis is supported by RNA data-mining, which identified Reticulon-1 as the sole ER-shaping protein consistently present in axonal transcriptomes and found it to be downregulated following cortical axon injury. Using compartmentalized microfluidic chambers, we demonstrate that local knockdown of Reticulon-1 mRNA enhances outgrowth while reducing the distal tubulin levels of injured cortical axons. Additionally, live cell imaging shows injury-induced reductions in microtubule growth rate and length, which are fully restored by axonal Reticulon-1 knockdown. Interestingly, axonal inhibition of the microtubule-severing protein Spastin fully prevents the effects of local Reticulon-1 knockdown on outgrowth and tubulin levels, while not affecting microtubule dynamics. Furthermore, we provide evidence supporting that the Reticulon-1C isoform is locally synthesized in injured axons and associates with Spastin to inhibit its severing activity. Our findings reveal a novel injury-dependent mechanism in which a locally synthesized ER-shaping protein lessens microtubule dynamics and the outgrowth of cortical axons.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-11DOI: 10.1101/2024.08.11.607076
Talya S Kramer, Flossie K Wan, Sarah M Pugliese, Adam A Atanas, Alex W Hiser, Jinyue Luo, Eric Bueno, Steven W Flavell
Complex behaviors like navigation rely on sequenced motor outputs that combine to generate effective movement. The brain-wide organization of the circuits that integrate sensory signals to select and execute appropriate motor sequences is not well understood. Here, we characterize the architecture of neural circuits that control C. elegans olfactory navigation. We identify error-correcting turns during navigation and use whole-brain calcium imaging and cell-specific perturbations to determine their neural underpinnings. These turns occur as motor sequences accompanied by neural sequences, in which defined neurons activate in a stereotyped order during each turn. Distinct neurons in this sequence respond to sensory cues, anticipate upcoming turn directions, and drive movement, linking key features of this sensorimotor behavior across time. The neuromodulator tyramine coordinates these sequential brain dynamics. Our results illustrate how neuromodulation can act on a defined neural architecture to generate sequential patterns of activity that link sensory cues to motor actions.
{"title":"Neural Sequences Underlying Directed Turning in C. elegans","authors":"Talya S Kramer, Flossie K Wan, Sarah M Pugliese, Adam A Atanas, Alex W Hiser, Jinyue Luo, Eric Bueno, Steven W Flavell","doi":"10.1101/2024.08.11.607076","DOIUrl":"https://doi.org/10.1101/2024.08.11.607076","url":null,"abstract":"Complex behaviors like navigation rely on sequenced motor outputs that combine to generate effective movement. The brain-wide organization of the circuits that integrate sensory signals to select and execute appropriate motor sequences is not well understood. Here, we characterize the architecture of neural circuits that control C. elegans olfactory navigation. We identify error-correcting turns during navigation and use whole-brain calcium imaging and cell-specific perturbations to determine their neural underpinnings. These turns occur as motor sequences accompanied by neural sequences, in which defined neurons activate in a stereotyped order during each turn. Distinct neurons in this sequence respond to sensory cues, anticipate upcoming turn directions, and drive movement, linking key features of this sensorimotor behavior across time. The neuromodulator tyramine coordinates these sequential brain dynamics. Our results illustrate how neuromodulation can act on a defined neural architecture to generate sequential patterns of activity that link sensory cues to motor actions.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-11DOI: 10.1101/2024.08.11.607487
Bo Dong, Quan Zhou, Peng Gao, Wei Jintao, Jiale Xiao, Wei Wang, Peipeng Liang, Danhua Lin, Hongjian He, Xi-Nian Zuo
Automated amygdala segmentation is one of the most common tasks in human neuroscience research. However, due to the small volume of the human amygdala, especially in developing brains, the precision and consistency of the segmentation results are often affected by individual differences and inconsistencies in data distribution. To address these challenges, we propose an algorithm for learning boundary contrast of 427 manually traced amygdalae in children and adolescents to generate a transformer, AmygdalaGo-BOLT3D, for automatic segmentation of human amygdala. This method focuses on the boundary to effectively address the issue of false positive recognition and inaccurate edges due to small amygdala volume. Firstly, AmygdalaGo-BOLT3D develops a basic architecture for an adaptive cooperation network with multiple granularities. Secondly, AmygdalaGo-BOLT3D builds the self-attention-based consistency module to address generalizability problems arising from individual differences and inconsistent data distributions. Third, AmygdalaGo-BOLT3D adapts the original sample-mask model for the amygdala scene, which consists of three parts, namely a lightweight volumetric feature encoder, a 3D cue encoder, and a volume mask decoder, to improve the generalized segmentation of the model. Finally, AmygdalaGo-BOLT3D implements a boundary contrastive learning framework that utilizes the interaction mechanism between a prior cue and the embedded magnetic resonance images to achieve effective integration between the two. Experimental results demonstrate that predictions of the overall structure and boundaries of the human amygdala exhibit highly improved precision and help maintain stability in multiple age groups and imaging centers. This verifies the stability and generalization of the algorithm designed for multiple tasks. AmygdalaGo-BOLT3D has been deployed for the community (GITHUB_LINK) to provide an open science foundation for its applications in population neuroscience.
{"title":"AmygdalaGo-BOLT3D: A boundary learning transformer for tracing human amygdala","authors":"Bo Dong, Quan Zhou, Peng Gao, Wei Jintao, Jiale Xiao, Wei Wang, Peipeng Liang, Danhua Lin, Hongjian He, Xi-Nian Zuo","doi":"10.1101/2024.08.11.607487","DOIUrl":"https://doi.org/10.1101/2024.08.11.607487","url":null,"abstract":"Automated amygdala segmentation is one of the most common tasks in human neuroscience research. However, due to the small volume of the human amygdala, especially in developing brains, the precision and consistency of the segmentation results are often affected by individual differences and inconsistencies in data distribution. To address these challenges, we propose an algorithm for learning boundary contrast of 427 manually traced amygdalae in children and adolescents to generate a transformer, AmygdalaGo-BOLT3D, for automatic segmentation of human amygdala. This method focuses on the boundary to effectively address the issue of false positive recognition and inaccurate edges due to small amygdala volume. Firstly, AmygdalaGo-BOLT3D develops a basic architecture for an adaptive cooperation network with multiple granularities. Secondly, AmygdalaGo-BOLT3D builds the self-attention-based consistency module to address generalizability problems arising from individual differences and inconsistent data distributions. Third, AmygdalaGo-BOLT3D adapts the original sample-mask model for the amygdala scene, which consists of three parts, namely a lightweight volumetric feature encoder, a 3D cue encoder, and a volume mask decoder, to improve the generalized segmentation of the model. Finally, AmygdalaGo-BOLT3D implements a boundary contrastive learning framework that utilizes the interaction mechanism between a prior cue and the embedded magnetic resonance images to achieve effective integration between the two. Experimental results demonstrate that predictions of the overall structure and boundaries of the human amygdala exhibit highly improved precision and help maintain stability in multiple age groups and imaging centers. This verifies the stability and generalization of the algorithm designed for multiple tasks. AmygdalaGo-BOLT3D has been deployed for the community (GITHUB_LINK) to provide an open science foundation for its applications in population neuroscience.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-11DOI: 10.1101/2024.08.05.604527
He Chen, Jun Kunimatsu, Tomomichi Oya, Yuri Imaizumi, Yukiko Hori, Masayuki Matsumoto, Yasuhiro Tsubo, Okihide Hikosaka, Takafumi Minamimoto, Yuji Naya, Hiroshi Yamada
Neural dynamics reflect canonical computations that relay and transform information in the brain. Previous studies have identified the neural population dynamics in many individual brain regions as a trajectory geometry in a low-dimensional neural space. However, whether these populations share particular geometric patterns across brain-wide neural populations remains unclear. Here, by mapping neural dynamics widely across temporal/frontal/limbic regions in the cortical and subcortical structures of monkeys, we show that 10 neural populations, including 2,500 neurons, propagate visual item information in a stochastic manner. We found that the visual inputs predominantly evoked rotational dynamics in the higher-order visual area, the TE and its downstream striatum tail, while curvy/straight dynamics appeared more frequently downstream in the orbitofrontal/hippocampal network. These geometric changes were not deterministic but rather stochastic according to their respective emergence rates. These results indicated that visual information propagates as a heterogeneous mixture of stochastic neural population signals in the brain.
{"title":"Formation of brain-wide neural geometry during visual item recognition in monkeys","authors":"He Chen, Jun Kunimatsu, Tomomichi Oya, Yuri Imaizumi, Yukiko Hori, Masayuki Matsumoto, Yasuhiro Tsubo, Okihide Hikosaka, Takafumi Minamimoto, Yuji Naya, Hiroshi Yamada","doi":"10.1101/2024.08.05.604527","DOIUrl":"https://doi.org/10.1101/2024.08.05.604527","url":null,"abstract":"Neural dynamics reflect canonical computations that relay and transform information in the brain. Previous studies have identified the neural population dynamics in many individual brain regions as a trajectory geometry in a low-dimensional neural space. However, whether these populations share particular geometric patterns across brain-wide neural populations remains unclear. Here, by mapping neural dynamics widely across temporal/frontal/limbic regions in the cortical and subcortical structures of monkeys, we show that 10 neural populations, including 2,500 neurons, propagate visual item information in a stochastic manner. We found that the visual inputs predominantly evoked rotational dynamics in the higher-order visual area, the TE and its downstream striatum tail, while curvy/straight dynamics appeared more frequently downstream in the orbitofrontal/hippocampal network. These geometric changes were not deterministic but rather stochastic according to their respective emergence rates. These results indicated that visual information propagates as a heterogeneous mixture of stochastic neural population signals in the brain.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-11DOI: 10.1101/2024.08.10.607449
Lei Zhang, Malcom Binns, Ricky Chow, Rahel Rabi, Nicole D. Anderson, Jing Lu, Morris Freedman, Claude Alain
Introduction: The diagnosis, prognosis, and management of amnestic mild cognitive impairment (aMCI) remains challenging. Early detection of aMCI is crucial for timely interventions. Method: This study combines scalp recordings of auditory, visual, and somatosensory stimuli with a flexible and interpretable support vector machine classification pipeline to differentiate individuals diagnosed with aMCI from healthy controls. Results: Event-related potentials (ERPs) and functional connectivity (FC) matrices from each modality successfully predicted aMCI. We got optimal classification accuracy (96.1%), sensitivity (97.7%) and specificity (94.3%) when combining information from all sensory conditions than when using information from a single modality. Reduced ERP amplitude, higher FC in frontal region which predicted worse cognitive performance, and lower FC in posterior regions from delta to alpha frequency in aMCI contributed to classification. Conclusions: The results highlight the clinical potential of sensory-evoked potentials in detecting aMCI, with optimal classification using both amplitude and oscillatory-based FC measures from multiple modalities.
简介失忆性轻度认知障碍（aMCI）的诊断、预后和管理仍然具有挑战性。早期发现轻度认知障碍对及时干预至关重要。研究方法本研究将听觉、视觉和体感刺激的头皮记录与灵活、可解释的支持向量机分类管道相结合，以区分被诊断为 aMCI 的个体和健康对照组。研究结果来自每种模式的事件相关电位（ERPs）和功能连接矩阵（FC）都能成功预测急性脑梗塞。与使用单一模式的信息相比，结合所有感官条件的信息可获得最佳的分类准确率（96.1%）、灵敏度（97.7%）和特异性（94.3%）。在 aMCI 中，ERP 振幅减小、额叶区域的 FC 较高，这预示着认知表现较差，而后部区域从 delta 到 alpha 频率的 FC 较低，这都有助于分类：这些结果凸显了感觉诱发电位在检测 aMCI 方面的临床潜力，使用多种模式的振幅和基于振荡的 FC 测量可进行最佳分类。
{"title":"Neural Mechanism Underlying Successful Classification of Amnestic Mild Cognitive Impairment Using Multi-Sensory-Evoked Potentials","authors":"Lei Zhang, Malcom Binns, Ricky Chow, Rahel Rabi, Nicole D. Anderson, Jing Lu, Morris Freedman, Claude Alain","doi":"10.1101/2024.08.10.607449","DOIUrl":"https://doi.org/10.1101/2024.08.10.607449","url":null,"abstract":"Introduction: The diagnosis, prognosis, and management of amnestic mild cognitive impairment (aMCI) remains challenging. Early detection of aMCI is crucial for timely interventions. Method: This study combines scalp recordings of auditory, visual, and somatosensory stimuli with a flexible and interpretable support vector machine classification pipeline to differentiate individuals diagnosed with aMCI from healthy controls. Results: Event-related potentials (ERPs) and functional connectivity (FC) matrices from each modality successfully predicted aMCI. We got optimal classification accuracy (96.1%), sensitivity (97.7%) and specificity (94.3%) when combining information from all sensory conditions than when using information from a single modality. Reduced ERP amplitude, higher FC in frontal region which predicted worse cognitive performance, and lower FC in posterior regions from delta to alpha frequency in aMCI contributed to classification.\u0000Conclusions: The results highlight the clinical potential of sensory-evoked potentials in detecting aMCI, with optimal classification using both amplitude and oscillatory-based FC measures from multiple modalities.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-11DOI: 10.1101/2024.08.11.607402
Raymond L Dunn, Caitriona Costello, Jackson M Borchardt, Daniel Yutaka Sprague, Grace C Chiu, Julia M Miller, Noelle L'Etoile, Saul Kato
We report the existence of a working memory system in the nematode C. elegans that is employed for deferred action in a sensory-guided decision-making process. We find that the turn direction of discrete reorientations during navigation is under sensory-guided control and relies on a working memory that can persist over an intervening behavioral sequence. This memory system is implemented by the phasic interaction of two distributed oscillatory dynamical components. The interaction of oscillatory neural ensembles may be a conserved primitive of cognition across the animal kingdom.
{"title":"Relative phase of distributed oscillatory dynamics implements a working memory in a simple brain","authors":"Raymond L Dunn, Caitriona Costello, Jackson M Borchardt, Daniel Yutaka Sprague, Grace C Chiu, Julia M Miller, Noelle L'Etoile, Saul Kato","doi":"10.1101/2024.08.11.607402","DOIUrl":"https://doi.org/10.1101/2024.08.11.607402","url":null,"abstract":"We report the existence of a working memory system in the nematode <em>C. elegans</em> that is employed for deferred action in a sensory-guided decision-making process. We find that the turn direction of discrete reorientations during navigation is under sensory-guided control and relies on a working memory that can persist over an intervening behavioral sequence. This memory system is implemented by the phasic interaction of two distributed oscillatory dynamical components. The interaction of oscillatory neural ensembles may be a conserved primitive of cognition across the animal kingdom.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-10DOI: 10.1101/2024.08.09.607193
Yiliu Wang, Christof Koch, Uygar Sümbül
Neurons display remarkable diversity in their anatomical, molecular, and physiological properties. Although observed stereotypy in subsets of neurons is a pillar of neuroscience, clustering in high-dimensional feature spaces, such as those defined by single cell RNA-seq data, is often inconclusive and cells seemingly occupy continuous, rather than discrete, regions. In the retina, a layered structure, neurons of the same discrete type avoid spatial proximity with each other. While this principle, which is independent of clustering in feature space, has been a gold standard for retinal cell types, its applicability to the cortex has been only sparsely explored. Here, we provide evidence for such a mosaic hypothesis by developing a statistical point process analysis framework for spatial transcriptomic data. We demonstrate spatial avoidance across many excitatory and inhibitory neuronal types. Spatial avoidance disappears when cell types are merged, potentially offering a gold standard metric for evaluating the purity of putative cell types.
{"title":"Spatial transcriptomic data reveals pure cell types via the mosaic hypothesis","authors":"Yiliu Wang, Christof Koch, Uygar Sümbül","doi":"10.1101/2024.08.09.607193","DOIUrl":"https://doi.org/10.1101/2024.08.09.607193","url":null,"abstract":"Neurons display remarkable diversity in their anatomical, molecular, and physiological properties. Although observed stereotypy in subsets of neurons is a pillar of neuroscience, clustering in high-dimensional feature spaces, such as those defined by single cell RNA-seq data, is often inconclusive and cells seemingly occupy continuous, rather than discrete, regions. In the retina, a layered structure, neurons of the same discrete type avoid spatial proximity with each other. While this principle, which is independent of clustering in feature space, has been a gold standard for retinal cell types, its applicability to the cortex has been only sparsely explored. Here, we provide evidence for such a mosaic hypothesis by developing a statistical point process analysis framework for spatial transcriptomic data. We demonstrate spatial avoidance across many excitatory and inhibitory neuronal types. Spatial avoidance disappears when cell types are merged, potentially offering a gold standard metric for evaluating the purity of putative cell types.","PeriodicalId":501581,"journal":{"name":"bioRxiv - Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：