Pub Date : 2020-07-08Epub Date: 2020-01-21DOI: 10.1146/annurev-neuro-101419-011117
John B Issa, Gilad Tocker, Michael E Hasselmo, James G Heys, Daniel A Dombeck
Interval timing, which operates on timescales of seconds to minutes, is distributed across multiple brain regions and may use distinct circuit mechanisms as compared to millisecond timing and circadian rhythms. However, its study has proven difficult, as timing on this scale is deeply entangled with other behaviors. Several circuit and cellular mechanisms could generate sequential or ramping activity patterns that carry timing information. Here we propose that a productive approach is to draw parallels between interval timing and spatial navigation, where direct analogies can be made between the variables of interest and the mathematical operations necessitated. Along with designing experiments that isolate or disambiguate timing behavior from other variables, new techniques will facilitate studies that directly address the neural mechanisms that are responsible for interval timing.
{"title":"Navigating Through Time: A Spatial Navigation Perspective on How the Brain May Encode Time.","authors":"John B Issa, Gilad Tocker, Michael E Hasselmo, James G Heys, Daniel A Dombeck","doi":"10.1146/annurev-neuro-101419-011117","DOIUrl":"10.1146/annurev-neuro-101419-011117","url":null,"abstract":"<p><p>Interval timing, which operates on timescales of seconds to minutes, is distributed across multiple brain regions and may use distinct circuit mechanisms as compared to millisecond timing and circadian rhythms. However, its study has proven difficult, as timing on this scale is deeply entangled with other behaviors. Several circuit and cellular mechanisms could generate sequential or ramping activity patterns that carry timing information. Here we propose that a productive approach is to draw parallels between interval timing and spatial navigation, where direct analogies can be made between the variables of interest and the mathematical operations necessitated. Along with designing experiments that isolate or disambiguate timing behavior from other variables, new techniques will facilitate studies that directly address the neural mechanisms that are responsible for interval timing.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351603/pdf/nihms-1583039.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37562949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2019-07-12DOI: 10.1146/annurev-neuro-070918-050421
Gord Fishell, Adam Kepecs
Cortical interneurons display striking differences in shape, physiology, and other attributes, challenging us to appropriately classify them. We previously suggested that interneuron types should be defined by their role in cortical processing. Here, we revisit the question of how to codify their diversity based upon their division of labor and function as controllers of cortical information flow. We suggest that developmental trajectories provide a guide for appreciating interneuron diversity and argue that subtype identity is generated using a configurational (rather than combinatorial) code of transcription factors that produce attractor states in the underlying gene regulatory network. We present our updated three-stage model for interneuron specification: an initial cardinal step, allocating interneurons into a few major classes, followed by definitive refinement, creating subclasses upon settling within the cortex, and lastly, state determination, reflecting the incorporation of interneurons into functional circuit ensembles. We close by discussing findings indicating that major interneuron classes are both evolutionarily ancient and conserved. We propose that the complexity of cortical circuits is generated by phylogenetically old interneuron types, complemented by an evolutionary increase in principal neuron diversity. This suggests that a natural neurobiological definition of interneuron types might be derived from a match between their developmental origin and computational function.
{"title":"Interneuron Types as Attractors and Controllers.","authors":"Gord Fishell, Adam Kepecs","doi":"10.1146/annurev-neuro-070918-050421","DOIUrl":"10.1146/annurev-neuro-070918-050421","url":null,"abstract":"<p><p>Cortical interneurons display striking differences in shape, physiology, and other attributes, challenging us to appropriately classify them. We previously suggested that interneuron types should be defined by their role in cortical processing. Here, we revisit the question of how to codify their diversity based upon their division of labor and function as controllers of cortical information flow. We suggest that developmental trajectories provide a guide for appreciating interneuron diversity and argue that subtype identity is generated using a configurational (rather than combinatorial) code of transcription factors that produce attractor states in the underlying gene regulatory network. We present our updated three-stage model for interneuron specification: an initial cardinal step, allocating interneurons into a few major classes, followed by definitive refinement, creating subclasses upon settling within the cortex, and lastly, state determination, reflecting the incorporation of interneurons into functional circuit ensembles. We close by discussing findings indicating that major interneuron classes are both evolutionarily ancient and conserved. We propose that the complexity of cortical circuits is generated by phylogenetically old interneuron types, complemented by an evolutionary increase in principal neuron diversity. This suggests that a natural neurobiological definition of interneuron types might be derived from a match between their developmental origin and computational function.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-070918-050421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37412619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-04-17DOI: 10.1146/annurev-neuro-070918-050452
Junchol Park, Luke T Coddington, Joshua T Dudman
Behavior is readily classified into patterns of movements with inferred common goals-actions. Goals may be discrete; movements are continuous. Through the careful study of isolated movements in laboratory settings, or via introspection, it has become clear that animals can exhibit exquisite graded specification to their movements. Moreover, graded control can be as fundamental to success as the selection of which action to perform under many naturalistic scenarios: a predator adjusting its speed to intercept moving prey, or a tool-user exerting the perfect amount of force to complete a delicate task. The basal ganglia are a collection of nuclei in vertebrates that extend from the forebrain (telencephalon) to the midbrain (mesencephalon), constituting a major descending extrapyramidal pathway for control over midbrain and brainstem premotor structures. Here we discuss how this pathway contributes to the continuous specification of movements that endows our voluntary actions with vigor and grace.
{"title":"Basal Ganglia Circuits for Action Specification.","authors":"Junchol Park, Luke T Coddington, Joshua T Dudman","doi":"10.1146/annurev-neuro-070918-050452","DOIUrl":"https://doi.org/10.1146/annurev-neuro-070918-050452","url":null,"abstract":"<p><p>Behavior is readily classified into patterns of movements with inferred common goals-actions. Goals may be discrete; movements are continuous. Through the careful study of isolated movements in laboratory settings, or via introspection, it has become clear that animals can exhibit exquisite graded specification to their movements. Moreover, graded control can be as fundamental to success as the selection of which action to perform under many naturalistic scenarios: a predator adjusting its speed to intercept moving prey, or a tool-user exerting the perfect amount of force to complete a delicate task. The basal ganglia are a collection of nuclei in vertebrates that extend from the forebrain (telencephalon) to the midbrain (mesencephalon), constituting a major descending extrapyramidal pathway for control over midbrain and brainstem premotor structures. Here we discuss how this pathway contributes to the continuous specification of movements that endows our voluntary actions with vigor and grace.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-070918-050452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37846273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-04-06DOI: 10.1146/annurev-neuro-100219-105424
David A McCormick, Dennis B Nestvogel, Biyu J He
Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.
{"title":"Neuromodulation of Brain State and Behavior.","authors":"David A McCormick, Dennis B Nestvogel, Biyu J He","doi":"10.1146/annurev-neuro-100219-105424","DOIUrl":"https://doi.org/10.1146/annurev-neuro-100219-105424","url":null,"abstract":"<p><p>Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-100219-105424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37805124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-02-26DOI: 10.1146/annurev-neuro-091619-022657
Melanie Maya Kaelberer, Laura E Rupprecht, Winston W Liu, Peter Weng, Diego V Bohórquez
Guided by sight, scent, texture, and taste, animals ingest food. Once ingested, it is up to the gut to make sense of the food's nutritional value. Classic sensory systems rely on neuroepithelial circuits to convert stimuli into signals that guide behavior. However, sensation of the gut milieu was thought to be mediated only by the passive release of hormones until the discovery of synapses in enteroendocrine cells. These are gut sensory epithelial cells, and those that form synapses are referred to as neuropod cells. Neuropod cells provide the foundation for the gut to transduce sensory signals from the intestinal milieu to the brain through fast neurotransmission onto neurons, including those of the vagus nerve. These findings have sparked a new field of exploration in sensory neurobiology-that of gut-brain sensory transduction.
{"title":"Neuropod Cells: The Emerging Biology of Gut-Brain Sensory Transduction.","authors":"Melanie Maya Kaelberer, Laura E Rupprecht, Winston W Liu, Peter Weng, Diego V Bohórquez","doi":"10.1146/annurev-neuro-091619-022657","DOIUrl":"10.1146/annurev-neuro-091619-022657","url":null,"abstract":"<p><p>Guided by sight, scent, texture, and taste, animals ingest food. Once ingested, it is up to the gut to make sense of the food's nutritional value. Classic sensory systems rely on neuroepithelial circuits to convert stimuli into signals that guide behavior. However, sensation of the gut milieu was thought to be mediated only by the passive release of hormones until the discovery of synapses in enteroendocrine cells. These are gut sensory epithelial cells, and those that form synapses are referred to as neuropod cells. Neuropod cells provide the foundation for the gut to transduce sensory signals from the intestinal milieu to the brain through fast neurotransmission onto neurons, including those of the vagus nerve. These findings have sparked a new field of exploration in sensory neurobiology-that of gut-brain sensory transduction.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7573801/pdf/nihms-1635794.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37680185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2019-12-24DOI: 10.1146/annurev-neuro-072116-031516
Brad K Hulse, Vivek Jayaraman
Many animals use an internal sense of direction to guide their movements through the world. Neurons selective to head direction are thought to support this directional sense and have been found in a diverse range of species, from insects to primates, highlighting their evolutionary importance. Across species, most head-direction networks share four key properties: a unique representation of direction at all times, persistent activity in the absence of movement, integration of angular velocity to update the representation, and the use of directional cues to correct drift. The dynamics of theorized network structures called ring attractors elegantly account for these properties, but their relationship to brain circuits is unclear. Here, we review experiments in rodents and flies that offer insights into potential neural implementations of ring attractor networks. We suggest that a theory-guided search across model systems for biological mechanisms that enable such dynamics would uncover general principles underlying head-direction circuit function.
{"title":"Mechanisms Underlying the Neural Computation of Head Direction.","authors":"Brad K Hulse, Vivek Jayaraman","doi":"10.1146/annurev-neuro-072116-031516","DOIUrl":"https://doi.org/10.1146/annurev-neuro-072116-031516","url":null,"abstract":"<p><p>Many animals use an internal sense of direction to guide their movements through the world. Neurons selective to head direction are thought to support this directional sense and have been found in a diverse range of species, from insects to primates, highlighting their evolutionary importance. Across species, most head-direction networks share four key properties: a unique representation of direction at all times, persistent activity in the absence of movement, integration of angular velocity to update the representation, and the use of directional cues to correct drift. The dynamics of theorized network structures called ring attractors elegantly account for these properties, but their relationship to brain circuits is unclear. Here, we review experiments in rodents and flies that offer insights into potential neural implementations of ring attractor networks. We suggest that a theory-guided search across model systems for biological mechanisms that enable such dynamics would uncover general principles underlying head-direction circuit function.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-072116-031516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37488102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-02-19DOI: 10.1146/annurev-neuro-100719-093305
Pablo M Paez, David A Lyons
Cells of the oligodendrocyte lineage express a wide range of Ca2+ channels and receptors that regulate oligodendrocyte progenitor cell (OPC) and oligodendrocyte formation and function. Here we define those key channels and receptors that regulate Ca2+ signaling and OPC development and myelination. We then discuss how the regulation of intracellular Ca2+ in turn affects OPC and oligodendrocyte biology in the healthy nervous system and under pathological conditions. Activation of Ca2+ channels and receptors in OPCs and oligodendrocytes by neurotransmitters converges on regulating intracellular Ca2+, making Ca2+ signaling a central candidate mediator of activity-driven myelination. Indeed, recent evidence indicates that localized changes in Ca2+ in oligodendrocytes can regulate the formation and remodeling of myelin sheaths and perhaps additional functions of oligodendrocytes and OPCs. Thus, decoding how OPCs and myelinating oligodendrocytes integrate and process Ca2+ signals will be important to fully understand central nervous system formation, health, and function.
{"title":"Calcium Signaling in the Oligodendrocyte Lineage: Regulators and Consequences.","authors":"Pablo M Paez, David A Lyons","doi":"10.1146/annurev-neuro-100719-093305","DOIUrl":"https://doi.org/10.1146/annurev-neuro-100719-093305","url":null,"abstract":"<p><p>Cells of the oligodendrocyte lineage express a wide range of Ca<sup>2+</sup> channels and receptors that regulate oligodendrocyte progenitor cell (OPC) and oligodendrocyte formation and function. Here we define those key channels and receptors that regulate Ca<sup>2+</sup> signaling and OPC development and myelination. We then discuss how the regulation of intracellular Ca<sup>2+</sup> in turn affects OPC and oligodendrocyte biology in the healthy nervous system and under pathological conditions. Activation of Ca<sup>2+</sup> channels and receptors in OPCs and oligodendrocytes by neurotransmitters converges on regulating intracellular Ca<sup>2+</sup>, making Ca<sup>2+</sup> signaling a central candidate mediator of activity-driven myelination. Indeed, recent evidence indicates that localized changes in Ca<sup>2+</sup> in oligodendrocytes can regulate the formation and remodeling of myelin sheaths and perhaps additional functions of oligodendrocytes and OPCs. Thus, decoding how OPCs and myelinating oligodendrocytes integrate and process Ca<sup>2+</sup> signals will be important to fully understand central nervous system formation, health, and function.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-100719-093305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37658965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-02-19DOI: 10.1146/annurev-neuro-090919-022842
Jeffrey C Magee, Christine Grienberger
Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.
{"title":"Synaptic Plasticity Forms and Functions.","authors":"Jeffrey C Magee, Christine Grienberger","doi":"10.1146/annurev-neuro-090919-022842","DOIUrl":"https://doi.org/10.1146/annurev-neuro-090919-022842","url":null,"abstract":"<p><p>Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-090919-022842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37658968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-02-21DOI: 10.1146/annurev-neuro-070918-050509
Peng Jin, Lily Yeh Jan, Yuh-Nung Jan
Activation of mechanosensitive ion channels underlies a variety of fundamental physiological processes that require sensation of mechanical force. Different mechanosensitive channels adapt distinctive structures and mechanotransduction mechanisms to fit their biological roles. How mechanosensitive channels work, especially in animals, has been extensively studied in the past decade. Here we review key findings in the functional and structural characterizations of these channels and highlight the structural features relevant to the mechanotransduction mechanism of each specific channel.
{"title":"Mechanosensitive Ion Channels: Structural Features Relevant to Mechanotransduction Mechanisms.","authors":"Peng Jin, Lily Yeh Jan, Yuh-Nung Jan","doi":"10.1146/annurev-neuro-070918-050509","DOIUrl":"https://doi.org/10.1146/annurev-neuro-070918-050509","url":null,"abstract":"<p><p>Activation of mechanosensitive ion channels underlies a variety of fundamental physiological processes that require sensation of mechanical force. Different mechanosensitive channels adapt distinctive structures and mechanotransduction mechanisms to fit their biological roles. How mechanosensitive channels work, especially in animals, has been extensively studied in the past decade. Here we review key findings in the functional and structural characterizations of these channels and highlight the structural features relevant to the mechanotransduction mechanism of each specific channel.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-070918-050509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37666401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-08Epub Date: 2020-02-25DOI: 10.1146/annurev-neuro-091319-024636
Josué Haubrich, Matteo Bernabo, Andrew G Baker, Karim Nader
An enduring problem in neuroscience is determining whether cases of amnesia result from eradication of the memory trace (storage impairment) or if the trace is present but inaccessible (retrieval impairment). The most direct approach to resolving this question is to quantify changes in the brain mechanisms of long-term memory (BM-LTM). This approach argues that if the amnesia is due to a retrieval failure, BM-LTM should remain at levels comparable to trained, unimpaired animals. Conversely, if memories are erased, BM-LTM should be reduced to resemble untrained levels. Here we review the use of BM-LTM in a number of studies that induced amnesia by targeting memory maintenance or reconsolidation. The literature strongly suggests that such amnesia is due to storage rather than retrieval impairments. We also describe the shortcomings of the purely behavioral protocol that purports to show recovery from amnesia as a method of understanding the nature of amnesia.
{"title":"Impairments to Consolidation, Reconsolidation, and Long-Term Memory Maintenance Lead to Memory Erasure.","authors":"Josué Haubrich, Matteo Bernabo, Andrew G Baker, Karim Nader","doi":"10.1146/annurev-neuro-091319-024636","DOIUrl":"https://doi.org/10.1146/annurev-neuro-091319-024636","url":null,"abstract":"<p><p>An enduring problem in neuroscience is determining whether cases of amnesia result from eradication of the memory trace (storage impairment) or if the trace is present but inaccessible (retrieval impairment). The most direct approach to resolving this question is to quantify changes in the brain mechanisms of long-term memory (BM-LTM). This approach argues that if the amnesia is due to a retrieval failure, BM-LTM should remain at levels comparable to trained, unimpaired animals. Conversely, if memories are erased, BM-LTM should be reduced to resemble untrained levels. Here we review the use of BM-LTM in a number of studies that induced amnesia by targeting memory maintenance or reconsolidation. The literature strongly suggests that such amnesia is due to storage rather than retrieval impairments. We also describe the shortcomings of the purely behavioral protocol that purports to show recovery from amnesia as a method of understanding the nature of amnesia.</p>","PeriodicalId":8008,"journal":{"name":"Annual review of neuroscience","volume":null,"pages":null},"PeriodicalIF":13.9,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-neuro-091319-024636","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37675708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}