Pub Date : 2022-12-07DOI: 10.1101/2022.12.07.519456
Sylvain L’Hermite, Benedikt Zoefel
Rhythmic entrainment echoes—rhythmic brain responses that outlast rhythmic stimulation—can demonstrate endogenous neural oscillations entrained by the stimulus rhythm. Here, we tested for such echoes in auditory perception. Participants detected a pure tone target, presented at a variable delay after another pure tone that was rhythmically modulated in amplitude. In four experiments involving 154 human (female and male) participants, we tested (1) which stimulus rate produces the strongest entrainment echo and, inspired by the tonotopical organization of the auditory system and findings in nonhuman primates, (2) whether these are organized according to sound frequency. We found the strongest entrainment echoes after 6 and 8 Hz stimulation, respectively. The best moments for target detection (in phase or antiphase with the preceding rhythm) depended on whether sound frequencies of entraining and target stimuli matched, which is in line with a tonotopical organization. However, for the same experimental condition, best moments were not always consistent across experiments. We provide a speculative explanation for these differences that relies on the notion that neural entrainment and repetition-related adaptation might exercise competing opposite influences on perception. Together, we find rhythmic echoes in auditory perception that seem more complex than those predicted from initial theories of neural entrainment. SIGNIFICANCE STATEMENT Rhythmic entrainment echoes are rhythmic brain responses that are produced by a rhythmic stimulus and persist after its offset. These echoes play an important role for the identification of endogenous brain oscillations, entrained by rhythmic stimulation, and give us insights into whether and how participants predict the timing of events. In four independent experiments involving >150 participants, we examined entrainment echoes in auditory perception. We found that entrainment echoes have a preferred rate (between 6 and 8 Hz) and seem to follow the tonotopic organization of the auditory system. Although speculative, we also found evidence that several, potentially competing processes might interact to produce such echoes, a notion that might need to be considered for future experimental design.
{"title":"Rhythmic Entrainment Echoes in Auditory Perception","authors":"Sylvain L’Hermite, Benedikt Zoefel","doi":"10.1101/2022.12.07.519456","DOIUrl":"https://doi.org/10.1101/2022.12.07.519456","url":null,"abstract":"Rhythmic entrainment echoes—rhythmic brain responses that outlast rhythmic stimulation—can demonstrate endogenous neural oscillations entrained by the stimulus rhythm. Here, we tested for such echoes in auditory perception. Participants detected a pure tone target, presented at a variable delay after another pure tone that was rhythmically modulated in amplitude. In four experiments involving 154 human (female and male) participants, we tested (1) which stimulus rate produces the strongest entrainment echo and, inspired by the tonotopical organization of the auditory system and findings in nonhuman primates, (2) whether these are organized according to sound frequency. We found the strongest entrainment echoes after 6 and 8 Hz stimulation, respectively. The best moments for target detection (in phase or antiphase with the preceding rhythm) depended on whether sound frequencies of entraining and target stimuli matched, which is in line with a tonotopical organization. However, for the same experimental condition, best moments were not always consistent across experiments. We provide a speculative explanation for these differences that relies on the notion that neural entrainment and repetition-related adaptation might exercise competing opposite influences on perception. Together, we find rhythmic echoes in auditory perception that seem more complex than those predicted from initial theories of neural entrainment. SIGNIFICANCE STATEMENT Rhythmic entrainment echoes are rhythmic brain responses that are produced by a rhythmic stimulus and persist after its offset. These echoes play an important role for the identification of endogenous brain oscillations, entrained by rhythmic stimulation, and give us insights into whether and how participants predict the timing of events. In four independent experiments involving >150 participants, we examined entrainment echoes in auditory perception. We found that entrainment echoes have a preferred rate (between 6 and 8 Hz) and seem to follow the tonotopic organization of the auditory system. Although speculative, we also found evidence that several, potentially competing processes might interact to produce such echoes, a notion that might need to be considered for future experimental design.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"52 1","pages":"6667 - 6678"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75893026","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 : 2022-12-03DOI: 10.1101/2022.12.02.518124
Omar A. Qureshi, Jessica Leake, A. Delaney, S. Killcross, R. Westbrook, Nathan M. Holmes
This study examined the effect of danger on consolidation of neutral information in two regions of the rat (male and female) medial temporal lobe: the perirhinal cortex (PRh) and basolateral amygdala complex (BLA). The neutral information was the association that forms between an auditory stimulus and a visual stimulus (labeled S2 and S1) across their pairings in sensory preconditioning. We show that, when the sensory preconditioning session is followed by a shocked context exposure, the danger shifts consolidation of the S2-S1 association from the PRh to the BLA; and does so by interacting with processes involved in encoding of the S2-S1 pairings. Specifically, we show that the initial S2-S1 pairing in sensory preconditioning is encoded in the BLA and not the PRh; whereas the later S2-S1 pairings are encoded in the PRh and not the BLA. When the sensory preconditioning session is followed by a context alone exposure, the BLA-dependent trace of the early S2-S1 pairings decays and the PRh-dependent trace of the later S2-S1 pairings is consolidated in memory. However, when the sensory preconditioning session is followed by a shocked context exposure, the PRh-dependent trace of the later S2-S1 pairings is suppressed and the BLA-dependent trace of the initial S2-S1 pairing is consolidated in memory. These findings are discussed with respect to mutually inhibitory interactions between the PRh and BLA, and the way that these regions support memory in other protocols, including recognition memory in people. SIGNIFICANCE STATEMENT The perirhinal cortex (PRh) and basolateral amygdala complex (BLA) process the pairings of neutral auditory and visual stimuli in sensory preconditioning. The involvement of each region in this processing is determined by the novelty/familiarity of the stimuli as well as events that occur immediately after the preconditioning session. Novel stimuli are represented in the BLA; however, as these stimuli are repeatedly presented without consequence, they come to be represented in the PRh. Whether the BLA- or PRh-dependent representation is consolidated in memory depends on what happens next. When nothing of significance occurs, the PRh-dependent representation is consolidated and the BLA-dependent representation decays; but when danger is encountered, the PRh-dependent representation is inhibited and the BLA-dependent representation is selected for consolidation.
{"title":"Danger Changes the Way the Brain Consolidates Neutral Information; and Does So by Interacting with Processes Involved in the Encoding of That Information","authors":"Omar A. Qureshi, Jessica Leake, A. Delaney, S. Killcross, R. Westbrook, Nathan M. Holmes","doi":"10.1101/2022.12.02.518124","DOIUrl":"https://doi.org/10.1101/2022.12.02.518124","url":null,"abstract":"This study examined the effect of danger on consolidation of neutral information in two regions of the rat (male and female) medial temporal lobe: the perirhinal cortex (PRh) and basolateral amygdala complex (BLA). The neutral information was the association that forms between an auditory stimulus and a visual stimulus (labeled S2 and S1) across their pairings in sensory preconditioning. We show that, when the sensory preconditioning session is followed by a shocked context exposure, the danger shifts consolidation of the S2-S1 association from the PRh to the BLA; and does so by interacting with processes involved in encoding of the S2-S1 pairings. Specifically, we show that the initial S2-S1 pairing in sensory preconditioning is encoded in the BLA and not the PRh; whereas the later S2-S1 pairings are encoded in the PRh and not the BLA. When the sensory preconditioning session is followed by a context alone exposure, the BLA-dependent trace of the early S2-S1 pairings decays and the PRh-dependent trace of the later S2-S1 pairings is consolidated in memory. However, when the sensory preconditioning session is followed by a shocked context exposure, the PRh-dependent trace of the later S2-S1 pairings is suppressed and the BLA-dependent trace of the initial S2-S1 pairing is consolidated in memory. These findings are discussed with respect to mutually inhibitory interactions between the PRh and BLA, and the way that these regions support memory in other protocols, including recognition memory in people. SIGNIFICANCE STATEMENT The perirhinal cortex (PRh) and basolateral amygdala complex (BLA) process the pairings of neutral auditory and visual stimuli in sensory preconditioning. The involvement of each region in this processing is determined by the novelty/familiarity of the stimuli as well as events that occur immediately after the preconditioning session. Novel stimuli are represented in the BLA; however, as these stimuli are repeatedly presented without consequence, they come to be represented in the PRh. Whether the BLA- or PRh-dependent representation is consolidated in memory depends on what happens next. When nothing of significance occurs, the PRh-dependent representation is consolidated and the BLA-dependent representation decays; but when danger is encountered, the PRh-dependent representation is inhibited and the BLA-dependent representation is selected for consolidation.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"131 1","pages":"2934 - 2949"},"PeriodicalIF":0.0,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81727860","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 : 2022-11-30DOI: 10.1523/JNEUROSCI.twij.42.48.2022
Karolynn, Hsu, Makiko, Yamada, J. P. Fawcett
MLLT11 is a 90 aa protein that was first identified because its gene was translocated and fused to the mixed-lineage leukemia (MLL) gene in two children with pediatric leukemia. MLLT11 has since been linked to several other cancers and has been shown to promote differentiation of hematopoietic precursors into T cells. Remarkably, the only other cell types that express MLLT11 are neurons of the PNS and CNS. The role of MLLT11 in neurons has been unknown, but StantonTurcotte et al. report that it contributes to migration and neurite outgrowth of cortical neurons. Expression of MLLT11 in the developing cerebral cortex increased as upper-layer pyramidal cells were generated and were beginning to migrate through the intermediate zone and lower layers of the cortical plate. Expression increased in the upper layers as they became populated with neurons, and expression declined starting around postnatal day 21. Knocking out MLLT11 selectively in newborn upper-layer neurons led to cortical thinning, and it slowed migration of upper-layer neurons. In contrast, overexpressing MLLT11 accelerated neuronal migration into the cortical plate. Knocking out MLLT11 also reduced neurite growth: upper-layer pyramidal neurons send projections to the contralateral hemisphere through the corpus callosum, and this structure was significantly smaller in MLLT11-deficient mice than in controls. And the dendritic arbors of MLLT11-deficient upper-layer pyramidal neurons were shorter and had fewer branches than normal. Pull-down assays revealed that MLLT11 was associated with several tubulin and myosin isoforms. Furthermore, MLLT11 colocalized with acetylated (stabilized) tubulin in cultured neurons. Notably, both neuronal migration and process extension depend strongly on microtubule dynamics. Therefore, MLLT11 may promote migration and neurite outgrowth by regulating microtubule stability. Stimulation of migration and process extension may also explain the link between MLLT11 and cancers, as these processes contribute to tissue invasion andmetastasis of tumor cells.
{"title":"This Week in The Journal","authors":"Karolynn, Hsu, Makiko, Yamada, J. P. Fawcett","doi":"10.1523/JNEUROSCI.twij.42.48.2022","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.42.48.2022","url":null,"abstract":"MLLT11 is a 90 aa protein that was first identified because its gene was translocated and fused to the mixed-lineage leukemia (MLL) gene in two children with pediatric leukemia. MLLT11 has since been linked to several other cancers and has been shown to promote differentiation of hematopoietic precursors into T cells. Remarkably, the only other cell types that express MLLT11 are neurons of the PNS and CNS. The role of MLLT11 in neurons has been unknown, but StantonTurcotte et al. report that it contributes to migration and neurite outgrowth of cortical neurons. Expression of MLLT11 in the developing cerebral cortex increased as upper-layer pyramidal cells were generated and were beginning to migrate through the intermediate zone and lower layers of the cortical plate. Expression increased in the upper layers as they became populated with neurons, and expression declined starting around postnatal day 21. Knocking out MLLT11 selectively in newborn upper-layer neurons led to cortical thinning, and it slowed migration of upper-layer neurons. In contrast, overexpressing MLLT11 accelerated neuronal migration into the cortical plate. Knocking out MLLT11 also reduced neurite growth: upper-layer pyramidal neurons send projections to the contralateral hemisphere through the corpus callosum, and this structure was significantly smaller in MLLT11-deficient mice than in controls. And the dendritic arbors of MLLT11-deficient upper-layer pyramidal neurons were shorter and had fewer branches than normal. Pull-down assays revealed that MLLT11 was associated with several tubulin and myosin isoforms. Furthermore, MLLT11 colocalized with acetylated (stabilized) tubulin in cultured neurons. Notably, both neuronal migration and process extension depend strongly on microtubule dynamics. Therefore, MLLT11 may promote migration and neurite outgrowth by regulating microtubule stability. Stimulation of migration and process extension may also explain the link between MLLT11 and cancers, as these processes contribute to tissue invasion andmetastasis of tumor cells.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"65 1","pages":"8914 - 8914"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77307806","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 : 2022-11-29DOI: 10.1101/2022.11.24.22282369
S. Mishra, D. Moore
Auditory experience plays a critical role in hearing development. Developmental auditory deprivation because of otitis media, a common childhood disease, produces long-standing changes in the central auditory system, even after the middle ear pathology is resolved. The effects of sound deprivation because of otitis media have been mostly studied in the ascending auditory system but remain to be examined in the descending pathway that runs from the auditory cortex to the cochlea via the brainstem. Alterations in the efferent neural system could be important because the descending olivocochlear pathway influences the neural representation of transient sounds in noise in the afferent auditory system and is thought to be involved in auditory learning. Here, we show that the inhibitory strength of the medial olivocochlear efferents is weaker in children with a documented history of otitis media relative to controls; both boys and girls were included in the study. In addition, children with otitis media history required a higher signal-to-noise ratio on a sentence-in-noise recognition task than controls to achieve the same criterion performance level. Poorer speech-in-noise recognition, a hallmark of impaired central auditory processing, was related to efferent inhibition, and could not be attributed to the middle ear or cochlear mechanics. SIGNIFICANCE STATEMENT Otitis media is the second most common reason children go to the doctor. Previously, degraded auditory experience because of otitis media has been associated with reorganized ascending neural pathways, even after middle ear pathology resolved. Here, we show that altered afferent auditory input because of otitis media during childhood is also associated with long-lasting reduced descending neural pathway function and poorer speech-in-noise recognition. These novel, efferent findings may be important for the detection and treatment of childhood otitis media.
{"title":"Auditory Deprivation during Development Alters Efferent Neural Feedback and Perception","authors":"S. Mishra, D. Moore","doi":"10.1101/2022.11.24.22282369","DOIUrl":"https://doi.org/10.1101/2022.11.24.22282369","url":null,"abstract":"Auditory experience plays a critical role in hearing development. Developmental auditory deprivation because of otitis media, a common childhood disease, produces long-standing changes in the central auditory system, even after the middle ear pathology is resolved. The effects of sound deprivation because of otitis media have been mostly studied in the ascending auditory system but remain to be examined in the descending pathway that runs from the auditory cortex to the cochlea via the brainstem. Alterations in the efferent neural system could be important because the descending olivocochlear pathway influences the neural representation of transient sounds in noise in the afferent auditory system and is thought to be involved in auditory learning. Here, we show that the inhibitory strength of the medial olivocochlear efferents is weaker in children with a documented history of otitis media relative to controls; both boys and girls were included in the study. In addition, children with otitis media history required a higher signal-to-noise ratio on a sentence-in-noise recognition task than controls to achieve the same criterion performance level. Poorer speech-in-noise recognition, a hallmark of impaired central auditory processing, was related to efferent inhibition, and could not be attributed to the middle ear or cochlear mechanics. SIGNIFICANCE STATEMENT Otitis media is the second most common reason children go to the doctor. Previously, degraded auditory experience because of otitis media has been associated with reorganized ascending neural pathways, even after middle ear pathology resolved. Here, we show that altered afferent auditory input because of otitis media during childhood is also associated with long-lasting reduced descending neural pathway function and poorer speech-in-noise recognition. These novel, efferent findings may be important for the detection and treatment of childhood otitis media.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"11 1","pages":"4642 - 4649"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86615371","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 : 2022-11-28DOI: 10.1101/2022.11.23.517746
Gabriela Ojeda Valencia, N. Gregg, Harvey Huang, B. Lundstrom, B. Brinkmann, T. Pal Attia, J. V. Van Gompel, M. Bernstein, M. In, J. Huston, G. Worrell, K. Miller, D. Hermes
Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the “limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave.” This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis. SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer’s disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the “limbic HAP-wave.” The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.
{"title":"Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System","authors":"Gabriela Ojeda Valencia, N. Gregg, Harvey Huang, B. Lundstrom, B. Brinkmann, T. Pal Attia, J. V. Van Gompel, M. Bernstein, M. In, J. Huston, G. Worrell, K. Miller, D. Hermes","doi":"10.1101/2022.11.23.517746","DOIUrl":"https://doi.org/10.1101/2022.11.23.517746","url":null,"abstract":"Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the “limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave.” This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis. SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer’s disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the “limbic HAP-wave.” The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"9 6 1","pages":"6697 - 6711"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76009128","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 : 2022-11-28DOI: 10.1101/2022.09.07.506943
O. Ferrante, A. Zhigalov, C. Hickey, O. Jensen
Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning. Here, we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression while concurrently investigating the modulation of posterior alpha band activity (8–12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the prestimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha band activity might subtend different and possibly independent attentional mechanisms. SIGNIFICANCE STATEMENT What we experienced in the past affects how we perceive the external world in the future. For example, an annoying flashing light might be better ignored if we know in advance where it usually appears. This ability of extracting regularities from the environment is called statistical learning. In this study, we explore the neuronal mechanisms allowing the attentional system to overlook items that are unequivocally distracting based on their spatial distribution. By recording brain activity using MEG while probing neural excitability with a novel technique called RIFT, we show that the neuronal excitability in early visual cortex is reduced in advance of stimulus presentation for locations where distracting items are more likely to occur.
{"title":"Statistical Learning of Distractor Suppression Downregulates Prestimulus Neural Excitability in Early Visual Cortex","authors":"O. Ferrante, A. Zhigalov, C. Hickey, O. Jensen","doi":"10.1101/2022.09.07.506943","DOIUrl":"https://doi.org/10.1101/2022.09.07.506943","url":null,"abstract":"Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning. Here, we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression while concurrently investigating the modulation of posterior alpha band activity (8–12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the prestimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha band activity might subtend different and possibly independent attentional mechanisms. SIGNIFICANCE STATEMENT What we experienced in the past affects how we perceive the external world in the future. For example, an annoying flashing light might be better ignored if we know in advance where it usually appears. This ability of extracting regularities from the environment is called statistical learning. In this study, we explore the neuronal mechanisms allowing the attentional system to overlook items that are unequivocally distracting based on their spatial distribution. By recording brain activity using MEG while probing neural excitability with a novel technique called RIFT, we show that the neuronal excitability in early visual cortex is reduced in advance of stimulus presentation for locations where distracting items are more likely to occur.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"41 1","pages":"2190 - 2198"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73533918","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 : 2022-11-24DOI: 10.1101/2022.11.23.517722
Alex Kunin, Jiahao Guo, K. Bassler, X. Pitkow, K. Josić
The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem, we applied novel community detection methods to analyze the synapse-level reconstruction of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically, and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts. Significance Statement The Hemibrain is a partial connectome of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Analyzing the structure of a network of this size requires novel and efficient computational tools. We applied a new community detection method to automatically uncover the modular structure in the Hemibrain dataset by maximizing a generalized modularity measure. This allowed us to resolve the community structure of the fly hemibrain at a range of spatial scales revealing a hierarchical organization of the network, where larger-scale modules are composed of smaller-scale structures. The method also allowed us to identify subnetworks with distinct cell and connectivity structures, such as the layered structures in the fan-shaped body, and the modular organization of the superior neuropil. Thus, network analysis methods can be adopted to the connectomes being reconstructed using modern experime
{"title":"Hierarchical Modular Structure of the Drosophila Connectome","authors":"Alex Kunin, Jiahao Guo, K. Bassler, X. Pitkow, K. Josić","doi":"10.1101/2022.11.23.517722","DOIUrl":"https://doi.org/10.1101/2022.11.23.517722","url":null,"abstract":"The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem, we applied novel community detection methods to analyze the synapse-level reconstruction of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically, and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts. Significance Statement The Hemibrain is a partial connectome of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Analyzing the structure of a network of this size requires novel and efficient computational tools. We applied a new community detection method to automatically uncover the modular structure in the Hemibrain dataset by maximizing a generalized modularity measure. This allowed us to resolve the community structure of the fly hemibrain at a range of spatial scales revealing a hierarchical organization of the network, where larger-scale modules are composed of smaller-scale structures. The method also allowed us to identify subnetworks with distinct cell and connectivity structures, such as the layered structures in the fan-shaped body, and the modular organization of the superior neuropil. Thus, network analysis methods can be adopted to the connectomes being reconstructed using modern experime","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"33 1","pages":"6384 - 6400"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80401135","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}
decreased the time constants of the two longest open states, and reduced the efficacy of transitions between the final closed state and the initial open state. These results demonstrate that auxiliary subunits can affect single-channel properties of GABA A Rs. Specifically, Shisa7 alters the kinetics of GABA A R channel gating during bursts. This effect explains the accelerated deactivation kinetics of GABA A Rs measured in previous whole-cell recordings. Together with previous work showing Shisa7 pro-motes surface expression of GABA A Rs, this study suggests that Shisa7 shapes inhibitory input to neurons by making whole-cell GABA currents larger in amplitude, but shorter in duration. This might be impor-tant for regulating spike timing.
减小了两个最长打开状态的时间常数，降低了最终关闭状态和初始打开状态之间的转换效率。这些结果表明，辅助亚基可以影响GABA A R的单通道特性。具体来说，Shisa7改变了GABA A R通道在爆发时的门控动力学。这一效应解释了在之前的全细胞记录中测量的GABA A Rs的加速失活动力学。结合先前的研究表明Shisa7促进GABA A Rs的表面表达，本研究表明Shisa7通过使全细胞GABA电流振幅更大，持续时间更短来塑造神经元的抑制性输入。这可能对调节尖峰时间很重要。
{"title":"This Week in The Journal","authors":"Kunwei Wu, Angelo, Keramidas, Wei Lu, Ryoichi, Nakamura","doi":"10.1523/JNEUROSCI.twij.42.47.2022","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.42.47.2022","url":null,"abstract":"decreased the time constants of the two longest open states, and reduced the efficacy of transitions between the final closed state and the initial open state. These results demonstrate that auxiliary subunits can affect single-channel properties of GABA A Rs. Specifically, Shisa7 alters the kinetics of GABA A R channel gating during bursts. This effect explains the accelerated deactivation kinetics of GABA A Rs measured in previous whole-cell recordings. Together with previous work showing Shisa7 pro-motes surface expression of GABA A Rs, this study suggests that Shisa7 shapes inhibitory input to neurons by making whole-cell GABA currents larger in amplitude, but shorter in duration. This might be impor-tant for regulating spike timing.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"10 1","pages":"8754 - 8754"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78335362","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 : 2022-11-22DOI: 10.1101/2022.11.22.517483
M. Gippert, Saskia Leupold, T. Heed, I. Howard, A. Villringer, V. Nikulin, B. Sehm
Many movements in daily life are embedded in motion sequences that involve more than one limb, demanding the motor system to monitor and control different body parts in quick succession. During such movements, systematic changes in the environment or the body might require motor adaptation of specific segments. However, previous motor adaptation research has focused primarily on motion sequences produced by a single limb, or on simultaneous movements of several limbs. For example, adaptation to opposing force fields is possible in unimanual reaching tasks when the direction of a prior or subsequent movement is predictive of force field direction. It is unclear, however, whether multilimb sequences can support motor adaptation processes in a similar way. In the present study (38 females, 38 males), we investigated whether reaches can be adapted to different force fields in a bimanual motor sequence when the information about the perturbation is associated with the prior movement direction of the other arm. In addition, we examined whether prior perceptual (visual or proprioceptive) feedback of the opposite arm contributes to force field-specific motor adaptation. Our key finding is that only active participation in the bimanual sequential task supports pronounced adaptation. This result suggests that active segments in bimanual motion sequences are linked across limbs. If there is a consistent association between movement kinematics of the linked and goal movement, the learning process of the goal movement can be facilitated. More generally, if motion sequences are repeated often, prior segments can evoke specific adjustments of subsequent movements. SIGNIFICANCE STATEMENT Movements in a limb's motion sequence can be adjusted based on linked movements. A prerequisite is that kinematics of the linked movements correctly predict which adjustments are needed. We show that use of kinematic information to improve performance is even possible when a prior linked movement is performed with a different limb. For example, a skilled juggler might have learned how to correctly adjust his catching movement of the left hand when the right hand performed a throwing action in a specific way. Linkage is possibly a key mechanism of the human motor system for learning complex bimanual skills. Our study emphasizes that learning of specific movements should not be studied in isolation but within their motor sequence context.
{"title":"Prior Movement of One Arm Facilitates Motor Adaptation in the Other","authors":"M. Gippert, Saskia Leupold, T. Heed, I. Howard, A. Villringer, V. Nikulin, B. Sehm","doi":"10.1101/2022.11.22.517483","DOIUrl":"https://doi.org/10.1101/2022.11.22.517483","url":null,"abstract":"Many movements in daily life are embedded in motion sequences that involve more than one limb, demanding the motor system to monitor and control different body parts in quick succession. During such movements, systematic changes in the environment or the body might require motor adaptation of specific segments. However, previous motor adaptation research has focused primarily on motion sequences produced by a single limb, or on simultaneous movements of several limbs. For example, adaptation to opposing force fields is possible in unimanual reaching tasks when the direction of a prior or subsequent movement is predictive of force field direction. It is unclear, however, whether multilimb sequences can support motor adaptation processes in a similar way. In the present study (38 females, 38 males), we investigated whether reaches can be adapted to different force fields in a bimanual motor sequence when the information about the perturbation is associated with the prior movement direction of the other arm. In addition, we examined whether prior perceptual (visual or proprioceptive) feedback of the opposite arm contributes to force field-specific motor adaptation. Our key finding is that only active participation in the bimanual sequential task supports pronounced adaptation. This result suggests that active segments in bimanual motion sequences are linked across limbs. If there is a consistent association between movement kinematics of the linked and goal movement, the learning process of the goal movement can be facilitated. More generally, if motion sequences are repeated often, prior segments can evoke specific adjustments of subsequent movements. SIGNIFICANCE STATEMENT Movements in a limb's motion sequence can be adjusted based on linked movements. A prerequisite is that kinematics of the linked movements correctly predict which adjustments are needed. We show that use of kinematic information to improve performance is even possible when a prior linked movement is performed with a different limb. For example, a skilled juggler might have learned how to correctly adjust his catching movement of the left hand when the right hand performed a throwing action in a specific way. Linkage is possibly a key mechanism of the human motor system for learning complex bimanual skills. Our study emphasizes that learning of specific movements should not be studied in isolation but within their motor sequence context.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"37 1","pages":"4341 - 4351"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81780882","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 : 2022-11-17DOI: 10.1101/2022.03.21.485172
L. C. Barne, Jonathan Giordano, T. Collins, Andrea Desantis
We are constantly sampling our environment by moving our eyes, but our subjective experience of the world is stable and constant. Stimulus displacement during or shortly after a saccade often goes unnoticed, a phenomenon called the saccadic suppression of displacement. Although we fail to notice such displacements, our oculomotor system computes the prediction errors and adequately adjusts the gaze and future saccadic execution, a phenomenon known as saccadic adaptation. In the present study, we aimed to find a brain signature of the trans-saccadic prediction error that informs the motor system but not explicit perception. We asked participants (either sex) to report whether a visual target was displaced during a saccade while recording electroencephalography (EEG). Using multivariate pattern analysis, we were able to differentiate displacements from no displacements, even when participants failed to report the displacement. In other words, we found that trans-saccadic prediction error is represented in the EEG signal 100 ms after the displacement presentation, mainly in occipital and parieto-occipital channels, even in the absence of explicit perception of the displacement. SIGNIFICANCE STATEMENT Stability in vision occurs even while performing saccades. One suggested mechanism for this counterintuitive visual phenomenon is that external displacement is suppressed during the retinal remapping caused by a saccade. Here, we shed light on the mechanisms of trans-saccadic stability by showing that displacement information is not entirely suppressed and specifically present in the early stages of visual processing. Such a signal is relevant and computed for oculomotor adjustment despite being neglected for perception.
{"title":"Decoding Trans-Saccadic Prediction Error","authors":"L. C. Barne, Jonathan Giordano, T. Collins, Andrea Desantis","doi":"10.1101/2022.03.21.485172","DOIUrl":"https://doi.org/10.1101/2022.03.21.485172","url":null,"abstract":"We are constantly sampling our environment by moving our eyes, but our subjective experience of the world is stable and constant. Stimulus displacement during or shortly after a saccade often goes unnoticed, a phenomenon called the saccadic suppression of displacement. Although we fail to notice such displacements, our oculomotor system computes the prediction errors and adequately adjusts the gaze and future saccadic execution, a phenomenon known as saccadic adaptation. In the present study, we aimed to find a brain signature of the trans-saccadic prediction error that informs the motor system but not explicit perception. We asked participants (either sex) to report whether a visual target was displaced during a saccade while recording electroencephalography (EEG). Using multivariate pattern analysis, we were able to differentiate displacements from no displacements, even when participants failed to report the displacement. In other words, we found that trans-saccadic prediction error is represented in the EEG signal 100 ms after the displacement presentation, mainly in occipital and parieto-occipital channels, even in the absence of explicit perception of the displacement. SIGNIFICANCE STATEMENT Stability in vision occurs even while performing saccades. One suggested mechanism for this counterintuitive visual phenomenon is that external displacement is suppressed during the retinal remapping caused by a saccade. Here, we shed light on the mechanisms of trans-saccadic stability by showing that displacement information is not entirely suppressed and specifically present in the early stages of visual processing. Such a signal is relevant and computed for oculomotor adjustment despite being neglected for perception.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"12 1","pages":"1933 - 1939"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79765852","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}
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