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How reduction of theta rhythm by medial septum inactivation may covary with disruption of entorhinal grid cell responses due to reduced cholinergic transmission.

Pilly PK, Grossberg S - Front Neural Circuits (2013)

Bottom Line: Two recent studies reduced the theta rhythm by inactivating the medial septum (MS) and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells.In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K(+)) and slow and medium after-hyperpolarization (sAHP and mAHP) channels.These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning and oscillatory dynamics.

View Article: PubMed Central - PubMed

Affiliation: Center for Neural and Emergent Systems, Information and Systems Sciences Laboratory, HRL Laboratories Malibu, CA, USA.

ABSTRACT
Oscillations in the coordinated firing of brain neurons have been proposed to play important roles in perception, cognition, attention, learning, navigation, and sensory-motor control. The network theta rhythm has been associated with properties of spatial navigation, as has the firing of entorhinal grid cells and hippocampal place cells. Two recent studies reduced the theta rhythm by inactivating the medial septum (MS) and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells. These results, along with properties of intrinsic membrane potential oscillations (MPOs) in slice preparations of medial entorhinal cortex (MEC), have been interpreted to support oscillatory interference models of grid cell firing. The current article shows that an alternative self-organizing map (SOM) model of grid cells can explain these data about intrinsic and network oscillations without invoking oscillatory interference. In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K(+)) and slow and medium after-hyperpolarization (sAHP and mAHP) channels. This alternative model can also explain data that are problematic for oscillatory interference models, including how knockout of the HCN1 gene in mice, which flattens the dorsoventral gradient in MPO frequency and resonance frequency, does not affect the development of the grid cell dorsoventral gradient of spatial scales, and how hexagonal grid firing fields in bats can occur even in the absence of theta band modulation. These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning and oscillatory dynamics.

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Macrocircuit of the Spectral Spacing model. Prior to the development period, entorhinal map cells receive unbiased axonal projections from stripe cells of multiple direction preferences, spatial phases, and spatial scales. Their response rates, or rates of temporal integration, help to select among the input spatial scales of stripe cells during the self-organized learning process that favors the categorical coding of the most frequent and energetic co-active input patterns. [Figure reprinted with permission from Grossberg and Pilly (2012)].
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Figure 2: Macrocircuit of the Spectral Spacing model. Prior to the development period, entorhinal map cells receive unbiased axonal projections from stripe cells of multiple direction preferences, spatial phases, and spatial scales. Their response rates, or rates of temporal integration, help to select among the input spatial scales of stripe cells during the self-organized learning process that favors the categorical coding of the most frequent and energetic co-active input patterns. [Figure reprinted with permission from Grossberg and Pilly (2012)].

Mentions: The current article provides an alternative, non-oscillatory account of the MS inactivation data (Brandon et al., 2011; Koenig et al., 2011), based on a SOM model of how grid cell receptive fields are learned during development (Grossberg and Pilly, 2012); see Figure 2. This SOM model has explained and simulated how the gradient of increasing spacing and size of grid cell receptive fields along the dorsoventral axis of MEC (Sargolini et al., 2006; Brun et al., 2008) can be learned as an emergent property of a decrease in cell response rate—that is, in rate of temporal integration (Garden et al., 2008)—along the dorsoventral axis. In particular, in response to inputs of multiple scales from stripe cells, grid cells with faster (slower) response rates can learn to selectively respond to stripe cells with smaller (larger) spatial scales. The kinetics of Ca2+-activated K+ slow and medium after-hyperpolarization potentials (sAHP and mAHP), which may be controlled by the rate of temporal integration, are proposed to play a critical role in biasing grid cells to learn a particular spatial scale of input stripe cells. Consistently, Navratilova et al. (2012) reported that the recovery time constants of mAHPs are longer for more ventral MEC layer II stellate cells.


How reduction of theta rhythm by medial septum inactivation may covary with disruption of entorhinal grid cell responses due to reduced cholinergic transmission.

Pilly PK, Grossberg S - Front Neural Circuits (2013)

Macrocircuit of the Spectral Spacing model. Prior to the development period, entorhinal map cells receive unbiased axonal projections from stripe cells of multiple direction preferences, spatial phases, and spatial scales. Their response rates, or rates of temporal integration, help to select among the input spatial scales of stripe cells during the self-organized learning process that favors the categorical coding of the most frequent and energetic co-active input patterns. [Figure reprinted with permission from Grossberg and Pilly (2012)].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814006&req=5

Figure 2: Macrocircuit of the Spectral Spacing model. Prior to the development period, entorhinal map cells receive unbiased axonal projections from stripe cells of multiple direction preferences, spatial phases, and spatial scales. Their response rates, or rates of temporal integration, help to select among the input spatial scales of stripe cells during the self-organized learning process that favors the categorical coding of the most frequent and energetic co-active input patterns. [Figure reprinted with permission from Grossberg and Pilly (2012)].
Mentions: The current article provides an alternative, non-oscillatory account of the MS inactivation data (Brandon et al., 2011; Koenig et al., 2011), based on a SOM model of how grid cell receptive fields are learned during development (Grossberg and Pilly, 2012); see Figure 2. This SOM model has explained and simulated how the gradient of increasing spacing and size of grid cell receptive fields along the dorsoventral axis of MEC (Sargolini et al., 2006; Brun et al., 2008) can be learned as an emergent property of a decrease in cell response rate—that is, in rate of temporal integration (Garden et al., 2008)—along the dorsoventral axis. In particular, in response to inputs of multiple scales from stripe cells, grid cells with faster (slower) response rates can learn to selectively respond to stripe cells with smaller (larger) spatial scales. The kinetics of Ca2+-activated K+ slow and medium after-hyperpolarization potentials (sAHP and mAHP), which may be controlled by the rate of temporal integration, are proposed to play a critical role in biasing grid cells to learn a particular spatial scale of input stripe cells. Consistently, Navratilova et al. (2012) reported that the recovery time constants of mAHPs are longer for more ventral MEC layer II stellate cells.

Bottom Line: Two recent studies reduced the theta rhythm by inactivating the medial septum (MS) and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells.In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K(+)) and slow and medium after-hyperpolarization (sAHP and mAHP) channels.These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning and oscillatory dynamics.

View Article: PubMed Central - PubMed

Affiliation: Center for Neural and Emergent Systems, Information and Systems Sciences Laboratory, HRL Laboratories Malibu, CA, USA.

ABSTRACT
Oscillations in the coordinated firing of brain neurons have been proposed to play important roles in perception, cognition, attention, learning, navigation, and sensory-motor control. The network theta rhythm has been associated with properties of spatial navigation, as has the firing of entorhinal grid cells and hippocampal place cells. Two recent studies reduced the theta rhythm by inactivating the medial septum (MS) and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells. These results, along with properties of intrinsic membrane potential oscillations (MPOs) in slice preparations of medial entorhinal cortex (MEC), have been interpreted to support oscillatory interference models of grid cell firing. The current article shows that an alternative self-organizing map (SOM) model of grid cells can explain these data about intrinsic and network oscillations without invoking oscillatory interference. In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K(+)) and slow and medium after-hyperpolarization (sAHP and mAHP) channels. This alternative model can also explain data that are problematic for oscillatory interference models, including how knockout of the HCN1 gene in mice, which flattens the dorsoventral gradient in MPO frequency and resonance frequency, does not affect the development of the grid cell dorsoventral gradient of spatial scales, and how hexagonal grid firing fields in bats can occur even in the absence of theta band modulation. These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning and oscillatory dynamics.

Show MeSH
Related in: MedlinePlus