A spatial memory task appropriate for electrophysiological recordings

Poe, Gina R.; Thompson, Carena M; Riley, Brett T.; Tysor, Michael K; Bjorness, Theresa E.; Steinhoff, Brianna P; Ferluga, Elizabeth D

doi:10.1016/s0165-0270(02)00233-9

Cited by 6 publications

(15 citation statements)

References 11 publications

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“…During this reactivation, the spatio-temporal patterning of neuronal activity is correlated with the patterning of the preceding awake activity (Louie & Wilson 2001). Furthermore, the correlation between cells co-active during waking is higher during sleep (Pavlides & Winson 1989;Wilson & McNaughton 1994;Poe et al 2002). We used a simple integrateand-fire based model to show that local strengthening of network connectivity underlies the formation of localized network heterogeneity, which, in turn, leads to rapidly increasing neuronal co-activation and potential formation of distributed memory representation.…”

Section: Modelling: Understanding the Structural Basis Of The Observementioning

confidence: 99%

Memory formation: from network structure to neural dynamics

Feldt

Wang²,

Hetrick

et al. 2010

Phil. Trans. R. Soc. A.

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Understanding the neural correlates of brain function is an extremely challenging task, since any cognitive process is distributed over a complex and evolving network of neurons that comprise the brain. In order to quantify observed changes in neuronal dynamics during hippocampal memory formation, we present metrics designed to detect directional interactions and the formation of functional neuronal ensembles. We apply these metrics to both experimental and model-derived data in an attempt to link anatomical network changes with observed changes in neuronal dynamics during hippocampal memory formation processes. We show that the developed model provides a consistent explanation of the anatomical network modifications that underlie the activity changes observed in the experimental data.

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Section: Modelling: Understanding the Structural Basis Of The Observementioning

confidence: 99%

Memory formation: from network structure to neural dynamics

Feldt

Wang²,

Hetrick

et al. 2010

Phil. Trans. R. Soc. A.

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show abstract

“…Single-unit recordings of CA1 hippocampal pyramidal cells were accomplished as in Gothard et al (1996) while the rat completed a spatial maze task (Poe et al, 2002) for food reward. Briefly, two adult male Fisher 344 rats were pre-trained to search for food on the 8-box rectangular maze with 3 of the 8 boxes baited with food.…”

Section: Experimental Designmentioning

confidence: 99%

“…For example, methods using optical imaging (Wu et al, 1994;Zochowski et al, 2000) or multiunit recordings with multi-electrode arrays (Potter, 2001), tetrodes (Gothard et al, 1996;Poe et al, 2002) or multiple single electrodes (Fries et al, 2001) all provide a measurement of neuronal activity at different locations simultaneously, allowing for the evaluation of distributed network activity.…”

Section: Introductionmentioning

confidence: 99%

“…Then, we compare Causal Entropies with cross-correlations, both applied to single-unit activity recorded from hippocampal CA1 pyramidal cells of freely behaving rats as they explored different spatial. During the recordings, the rats performed a spatial memory task (Poe et al, 2002), which is known to activate hippocampal populations and to require the hippocampus to dynamically change functional interconnected circuitries as the animals learn (see Shapiro, 2001 for review). We show a pair-wise increase in the asymmetric temporal interdependence between neurons when a novel environment is presented to the animal, which could be directly indicative of increased activity-dependent plasticity between the neurons.…”

Section: Introductionmentioning

confidence: 99%

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Causal entropies—A measure for determining changes in the temporal organization of neural systems

Waddell

Dzakpasu

Booth

et al. 2007

Journal of Neuroscience Methods

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We propose a novel measure to detect temporal ordering in the activity of individual neurons in a local network, which is thought to be a hallmark of activity-dependent synaptic modifications during learning. The measure, called Causal Entropy, is based on the time-adaptive detection of asymmetries in the relative temporal patterning between neuronal pairs. We characterize properties of the measure on both simulated data and experimental multiunit recordings of hippocampal neurons from the awake, behaving rat, and show that the metric can more readily detect those asymmetries than standard cross correlation-based techniques, especially since the temporal sensitivity of causal entropy can detect such changes rapidly and dynamically.

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“…The spatio-temporal patterning of neuronal activity during reactivation is correlated with the patterning of the preceding wake activity [4] and the correlation between cells coactive during waking is also higher during sleep [5,15,17,18]. It is widely thought that this reactivation serves as a mechanism of memory consolidation [8,19,20].…”

Section: Introductionmentioning

confidence: 99%