Signatures of rapid synaptic learning in the hippocampus during novel experiences

Neurons in the hippocampus exhibit striking selectivity for specific combinations of sensory features, forming representations which are thought to subserve episodic memory. Even during a completely novel experience, ensembles of hippocampal ``place cells'' are rapidly configured such that the population sparsely encodes visited locations, stabilizing within minutes of the first exposure to a new environment. What cellular mechanisms enable this fast encoding of experience? Here we leverage virtual reality and large scale neural recordings to dissect the effects of novelty and experience on the dynamics of place field formation. We show that the place fields of many CA1 neurons transiently shift locations and modulate the amplitude of their activity immediately after place field formation, consistent with rapid plasticity mechanisms driven by plateau potentials and somatic burst spiking. These motifs were particularly enriched during initial exploration of a novel context and decayed with experience. Our data suggest that novelty modulates the effective learning rate in CA1, favoring burst-driven field formation to support fast synaptic updating during new experience.

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Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments

eLife ◽

10.7554/elife.23040 ◽

2017 ◽

Vol 6 ◽

Cited By ~ 43

Author(s):

Jeremy D Cohen ◽

Mark Bolstad ◽

Albert K Lee

Keyword(s):

Virtual Environments ◽

Place Field ◽

Ca1 Neurons ◽

Long Term Storage ◽

Hippocampal Ca1 ◽

Field Activity ◽

Field Formation ◽

Complex Spikes ◽

Term Storage

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude – often suddenly – during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience – both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage.

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Building a Culture of Ethical, Comparable, Authentic Assessment

The Oxford Handbook of Philosophical and Qualitative Assessment in Music Education ◽

10.1093/oxfordhb/9780190265182.013.35 ◽

2019 ◽

pp. 463-481

Author(s):

Andrew Reid ◽

Julie Ballantyne

Keyword(s):

Teaching And Learning ◽

Large Scale ◽

Authentic Assessment ◽

Subject Area ◽

Music Educators ◽

System Level ◽

Diverse Range ◽

Effective Learning ◽

School Based ◽

The Subject

In an ideal world, assessment should be synonymous with effective learning and reflect the intricacies of the subject area. It should also be aligned with the ideals of education: to provide equitable opportunities for all students to achieve and to allow both appropriate differentiation for varied contexts and students and comparability across various contexts and students. This challenge is made more difficult in circumstances in which the contexts are highly heterogeneous, for example in the state of Queensland, Australia. Assessment in music challenges schooling systems in unique ways because teaching and learning in music are often naturally differentiated and diverse, yet assessment often calls for standardization. While each student and teacher has individual, evolving musical pathways in life, the syllabus and the system require consistency and uniformity. The challenge, then, is to provide diverse, equitable, and quality opportunities for all children to learn and achieve to the best of their abilities. This chapter discusses the designing and implementation of large-scale curriculum as experienced in secondary schools in Queensland, Australia. The experiences detailed explore the possibilities offered through externally moderated school-based assessment. Also discussed is the centrality of system-level clarity of purpose, principles and processes, and the provision of supportive networks and mechanisms to foster autonomy for a diverse range of music educators and contexts. Implications for education systems that desire diversity, equity, and quality are discussed, and the conclusion provokes further conceptualization and action on behalf of students, teachers, and the subject area of music.

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Robust information routing by dorsal subiculum neurons

Science Advances ◽

10.1126/sciadv.abf1913 ◽

2021 ◽

Vol 7 (11) ◽

pp. eabf1913

Author(s):

Takuma Kitanishi ◽

Ryoko Umaba ◽

Kenji Mizuseki

Keyword(s):

Nucleus Accumbens ◽

Large Scale ◽

Dorsal Hippocampus ◽

Retrosplenial Cortex ◽

Projection Neurons ◽

Target Region ◽

Ca1 Neurons ◽

Axonal Projections ◽

Output Structure ◽

Hippocampal Ca1

The dorsal hippocampus conveys various information associated with spatial navigation; however, how the information is distributed to multiple downstream areas remains unknown. We investigated this by identifying axonal projections using optogenetics during large-scale recordings from the rat subiculum, the major hippocampal output structure. Subicular neurons demonstrated a noise-resistant representation of place, speed, and trajectory, which was as accurate as or even more accurate than that of hippocampal CA1 neurons. Speed- and trajectory-dependent firings were most prominent in neurons projecting to the retrosplenial cortex and nucleus accumbens, respectively. Place-related firing was uniformly observed in neurons targeting the retrosplenial cortex, nucleus accumbens, anteroventral thalamus, and medial mammillary body. Theta oscillations and sharp-wave/ripples tightly controlled the firing of projection neurons in a target region–specific manner. In conclusion, the dorsal subiculum robustly routes diverse navigation-associated information to downstream areas.

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Building population models for large-scale neural recordings: Opportunities and pitfalls

Current Opinion in Neurobiology ◽

10.1016/j.conb.2021.07.003 ◽

2021 ◽

Vol 70 ◽

pp. 64-73

Author(s):

Cole Hurwitz ◽

Nina Kudryashova ◽

Arno Onken ◽

Matthias H. Hennig

Keyword(s):

Large Scale ◽

Population Models ◽

Neural Recordings

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Effective Neuronal Learning with Ineffective Hebbian Learning Rules

Neural Computation ◽

10.1162/089976601300014367 ◽

2001 ◽

Vol 13 (4) ◽

pp. 817-840 ◽

Cited By ~ 15

Author(s):

Gal Chechik ◽

Isaac Meilijson ◽

Eytan Ruppin

Keyword(s):

Hebbian Learning ◽

Memory Capacity ◽

Network Size ◽

Memory Storage ◽

Effective Learning ◽

Regulatory Processes ◽

Level Information ◽

Zero Sum ◽

Synaptic Learning ◽

Weight Correction

In this article we revisit the classical neuroscience paradigm of Hebbian learning. We find that it is difficult to achieve effective associative memory storage by Hebbian synaptic learning, since it requires network-level information at the synaptic level or sparse coding level. Effective learning can yet be achieved even with nonsparse patterns by a neuronal process that maintains a zero sum of the incoming synaptic efficacies. This weight correction improves the memory capacity of associative networks from an essentially bounded one to a memory capacity that scales linearly with network size. It also enables the effective storage of patterns with multiple levels of activity within a single network. Such neuronal weight correction can be successfully carried out by activity-dependent homeostasis of the neuron's synaptic efficacies, which was recently observed in cortical tissue. Thus, our findings suggest that associative learning by Hebbian synaptic learning should be accompanied by continuous remodeling of neuronally driven regulatory processes in the brain.

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T-SNE visualization of large-scale neural recordings

10.1101/087395 ◽

2016 ◽

Cited By ~ 5

Author(s):

George Dimitriadis ◽

Joana Neto ◽

Adam R. Kampff

Keyword(s):

Large Scale ◽

New Technologies ◽

Dimensional Space ◽

Clustering Algorithms ◽

Brain Regions ◽

Data Sets ◽

Neural Recordings ◽

Sorting Problem ◽

Feature Spaces ◽

High Degree

AbstractElectrophysiology is entering the era of ‘Big Data’. Multiple probes, each with hundreds to thousands of individual electrodes, are now capable of simultaneously recording from many brain regions. The major challenge confronting these new technologies is transforming the raw data into physiologically meaningful signals, i.e. single unit spikes. Sorting the spike events of individual neurons from a spatiotemporally dense sampling of the extracellular electric field is a problem that has attracted much attention [22, 23], but is still far from solved. Current methods still rely on human input and thus become unfeasible as the size of the data sets grow exponentially.Here we introduce the t-student stochastic neighbor embedding (t-sne) dimensionality reduction method [27] as a visualization tool in the spike sorting process. T-sne embeds the n-dimensional extracellular spikes (n = number of features by which each spike is decomposed) into a low (usually two) dimensional space. We show that such embeddings, even starting from different feature spaces, form obvious clusters of spikes that can be easily visualized and manually delineated with a high degree of precision. We propose that these clusters represent single units and test this assertion by applying our algorithm on labeled data sets both from hybrid [23] and paired juxtacellular/extracellular recordings [15]. We have released a graphical user interface (gui) written in python as a tool for the manual clustering of the t-sne embedded spikes and as a tool for an informed overview and fast manual curration of results from other clustering algorithms. Furthermore, the generated visualizations offer evidence in favor of the use of probes with higher density and smaller electrodes. They also graphically demonstrate the diverse nature of the sorting problem when spikes are recorded with different methods and arise from regions with different background spiking statistics.

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Distinct roles of visual, parietal, and frontal motor cortices in memory-guided sensorimotor decisions

eLife ◽

10.7554/elife.13764 ◽

2016 ◽

Vol 5 ◽

Cited By ~ 97

Author(s):

Michael J Goard ◽

Gerald N Pho ◽

Jonathan Woodson ◽

Mriganka Sur

Keyword(s):

Calcium Imaging ◽

Large Scale ◽

Behavioral Choice ◽

Population Analyses ◽

Delay Response ◽

Sensory Features ◽

Posterior Parietal ◽

Stimulus Identity ◽

Motor Actions

Mapping specific sensory features to future motor actions is a crucial capability of mammalian nervous systems. We investigated the role of visual (V1), posterior parietal (PPC), and frontal motor (fMC) cortices for sensorimotor mapping in mice during performance of a memory-guided visual discrimination task. Large-scale calcium imaging revealed that V1, PPC, and fMC neurons exhibited heterogeneous responses spanning all task epochs (stimulus, delay, response). Population analyses demonstrated unique encoding of stimulus identity and behavioral choice information across regions, with V1 encoding stimulus, fMC encoding choice even early in the trial, and PPC multiplexing the two variables. Optogenetic inhibition during behavior revealed that all regions were necessary during the stimulus epoch, but only fMC was required during the delay and response epochs. Stimulus identity can thus be rapidly transformed into behavioral choice, requiring V1, PPC, and fMC during the transformation period, but only fMC for maintaining the choice in memory prior to execution.

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