scholarly journals Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

2015 ◽  
Vol 9 ◽  
Author(s):  
Katie A. Ferguson ◽  
Carey Y. L. Huh ◽  
Bénédicte Amilhon ◽  
Frédéric Manseau ◽  
Sylvain Williams ◽  
...  
Keyword(s):  
Network Models ◽  
Cell Interactions ◽  
Theta Oscillations ◽  
Hippocampal Ca1 ◽  
Bistratified Cell

scholarly journals Alternating sequences of future and past behavior encoded within hippocampal theta oscillations

Science ◽  
2020 ◽  
Vol 370 (6513) ◽  
pp. 247-250 ◽  
Author(s):  
Mengni Wang ◽  
David J. Foster ◽  
Brad E. Pfeiffer
Keyword(s):  
Activity Patterns ◽  
Place Cells ◽  
Theta Oscillations ◽  
Retrospective Evaluation ◽  
Past Behavior ◽  
Hippocampal Ca1 ◽  
Ongoing Behavior ◽  
Theta Phase ◽  
Hippocampal Theta ◽  
And Storage

Neural networks display the ability to transform forward-ordered activity patterns into reverse-ordered, retrospective sequences. The mechanisms underlying this transformation remain unknown. We discovered that, during active navigation, rat hippocampal CA1 place cell ensembles are inherently organized to produce independent forward- and reverse-ordered sequences within individual theta oscillations. This finding may provide a circuit-level basis for retrospective evaluation and storage during ongoing behavior. Theta phase procession arose in a minority of place cells, many of which displayed two preferred firing phases in theta oscillations and preferentially participated in reverse replay during subsequent rest. These findings reveal an unexpected aspect of theta-based hippocampal encoding and provide a biological mechanism to support the expression of reverse-ordered sequences.

scholarly journals Local generation of multineuronal spike sequences in the hippocampal CA1 region

2015 ◽  
Vol 112 (33) ◽  
pp. 10521-10526 ◽  
Author(s):  
Eran Stark ◽  
Lisa Roux ◽  
Ronny Eichler ◽  
György Buzsáki
Keyword(s):  
High Frequency ◽  
Single Neuron ◽  
Theta Oscillations ◽  
Ca1 Region ◽  
Hippocampal Ca1 Region ◽  
High Frequency Oscillations ◽  
Hippocampal Ca1 ◽  
Spike Sequences ◽  
Freely Moving ◽  
Local Generation

Sequential activity of multineuronal spiking can be observed during theta and high-frequency ripple oscillations in the hippocampal CA1 region and is linked to experience, but the mechanisms underlying such sequences are unknown. We compared multineuronal spiking during theta oscillations, spontaneous ripples, and focal optically induced high-frequency oscillations (“synthetic” ripples) in freely moving mice. Firing rates and rate modulations of individual neurons, and multineuronal sequences of pyramidal cell and interneuron spiking, were correlated during theta oscillations, spontaneous ripples, and synthetic ripples. Interneuron spiking was crucial for sequence consistency. These results suggest that participation of single neurons and their sequential order in population events are not strictly determined by extrinsic inputs but also influenced by local-circuit properties, including synapses between local neurons and single-neuron biophysics.

scholarly journals Prefrontal cortical activity predicts the extra-place field spiking of hippocampal place cells

2020 ◽  
Author(s):  
Jai Y. Yu ◽  
Loren M. Frank
Keyword(s):  
Receptive Field ◽  
Receptive Fields ◽  
Cortical Activity ◽  
Place Cells ◽  
Theta Oscillations ◽  
Place Field ◽  
Prefrontal Cortical ◽  
Hippocampal Ca1 ◽  
Non Local ◽  
Hippocampal Theta

AbstractThe receptive field of a neuron describes the regions of a stimulus space where the neuron is consistently active. Sparse spiking outside of the receptive field is often considered to be noise, rather than a reflection of information processing. Whether this characterization is accurate remains unclear. We therefore contrasted the sparse, temporally isolated spiking of hippocampal CA1 place cells to the consistent, temporally adjacent spiking seen within their spatial receptive fields (“place fields”). We found that isolated spikes, which occur during locomotion, are more strongly phase coupled to hippocampal theta oscillations than adjacent spikes and, surprisingly, transiently express coherent representations of non-local spatial representations. Further, prefrontal cortical activity is coordinated with, and can predict the occurrence of future isolated spiking events. Rather than local noise within the hippocampus, sparse, isolated place cell spiking reflects a coordinated cortical-hippocampal process consistent with the generation of non-local scenario representations during active navigation.

scholarly journals The structure of hippocampal CA1 interactions optimizes spatial coding across experience

2021 ◽  
Author(s):  
Michele Nardin ◽  
Jozsef Csicsvari ◽  
Gašper Tkačik ◽  
Cristina Savin
Keyword(s):  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Cell Interactions ◽  
Statistical Estimator ◽  
Spatial Coding ◽  
Efficient Coding ◽  
Maximum Entropy Models ◽  
Hippocampal Ca1 ◽  
Central Brain ◽  
Neural Interactions

Although much is known about how single neurons in the hippocampus represent an animal’s position, how cell-cell interactions contribute to spatial coding remains poorly understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the signal-to-noise ratio of their spatial inputs. Moreover, the topology of the interactions facilitates linear decodability, making the information easy to read out by downstream circuits. These findings suggest that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.

scholarly journals Network models provide insight into how oriens-lacunosum-moleculare (OLM) and bistratified cell (BSC) interactions influence local CA1 theta rhythms

2014 ◽  
Vol 15 (Suppl 1) ◽  
pp. P42
Author(s):  
Katie A Ferguson ◽  
Carey YL Huh ◽  
Bénédicte Amilhon ◽  
Sylvain Williams ◽  
Frances K Skinner
Keyword(s):  
Network Models ◽  
Bistratified Cell ◽  
Insight Into

scholarly journals Prefrontal cortical activity predicts the occurrence of nonlocal hippocampal representations during spatial navigation

PLoS Biology ◽  
2021 ◽  
Vol 19 (9) ◽  
pp. e3001393
Author(s):  
Jai Y. Yu ◽  
Loren M. Frank
Keyword(s):  
Receptive Field ◽  
Receptive Fields ◽  
Cortical Activity ◽  
Place Cells ◽  
Theta Oscillations ◽  
Spatial Representations ◽  
Stimulus Space ◽  
Prefrontal Cortical ◽  
Hippocampal Ca1 ◽  
Hippocampal Theta

The receptive field of a neuron describes the regions of a stimulus space where the neuron is consistently active. Sparse spiking outside of the receptive field is often considered to be noise, rather than a reflection of information processing. Whether this characterization is accurate remains unclear. We therefore contrasted the sparse, temporally isolated spiking of hippocampal CA1 place cells to the consistent, temporally adjacent spiking seen within their spatial receptive fields (“place fields”). We found that isolated spikes, which occur during locomotion, are strongly phase coupled to hippocampal theta oscillations and transiently express coherent nonlocal spatial representations. Further, prefrontal cortical activity is coordinated with and can predict the occurrence of future isolated spiking events. Rather than local noise within the hippocampus, sparse, isolated place cell spiking reflects a coordinated cortical–hippocampal process consistent with the generation of nonlocal scenario representations during active navigation.

Analysis of Recordings of Single-Unit Firing and Population Activity in the Dorsal Subiculum of Unrestrained, Freely Moving Rats

2003 ◽  
Vol 90 (2) ◽  
pp. 655-665 ◽  
Author(s):  
Michael I. Anderson ◽  
Shane M. O'Mara
Keyword(s):  
Neuronal Activity ◽  
Hippocampal Formation ◽  
Theta Oscillations ◽  
Population Activity ◽  
Male Adult ◽  
Sharp Waves ◽  
Hippocampal Ca1 ◽  
Ongoing Behavior ◽  
Restricted Environment ◽  
Fast Spiking

We examined neuronal activity in the dorsal subiculum of unrestrained, male adult Wistar rats, which were implanted with a moveable eight-electrode microdrive. The subiculum is the primary hippocampal formation output area and is comparatively uninvestigated neurophysiologically. We compared subicular unit activity and the subicular EEG while rats occupied a small, restricted environment and also correlated neuronal activity with the ongoing behavior of the animal. Units were separated using their electrophysiological characteristics into bursting units, regular spiking units, theta-modulated units, and fast spiking units. The bursting and regular spiking unit classes are similar to hippocampal CA1 units, whereas the fast spiking units appear to be interneurons. Bursting units were variable in their behavior: some units bursted regularly, and others bursted only occasionally. Theta-modulated units have not been described before; these were similar to regular spiking units in all respects except that they increased their firing significantly when theta oscillations were present in the simultaneous EEG record. Subicular EEG was similar to hippocampal EEG, with theta oscillations dominating “alert, moving” behaviors, while large amplitude irregular activity (LIA), which included sharp waves, predominated when theta oscillations were not present, mainly during “alert, still” and “quiet” behaviors. A relatively small proportion of subicular recordings (approximately 32%) were phase-locked to theta; this is a smaller proportion than in areas from which the subiculum takes major inputs. The relative lack of entrainment of subicular neurons by this important intrinsic rhythm is suggestive of a limit to which theta might be capable of affecting both subicular and hippocampal information processing more generally.

What's in a model? Network models as tools instead of representations of what psychiatric disorders really are

2019 ◽  
Vol 42 ◽  
Author(s):  
Hanna M. van Loo ◽  
Jan-Willem Romeijn
Keyword(s):  
Psychiatric Disorders ◽  
Network Models ◽  
Model Network

AbstractNetwork models block reductionism about psychiatric disorders only if models are interpreted in a realist manner – that is, taken to represent “what psychiatric disorders really are.” A flexible and more instrumentalist view of models is needed to improve our understanding of the heterogeneity and multifactorial character of psychiatric disorders.

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