Limits...
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.

Show MeSH

Related in: MedlinePlus

Firing of model grid cells in non-preferred positions during MS inactivation (Case 4). Panels (A) and (B) highlight the differential spatial and temporal responses of two model grid cells with the smaller and larger scales, respectively, between the baseline trial and the inactivation trial. Note for this case the model animal ran along the same realistic trajectory and the bottom-up synaptic weights from stripe cells were not allowed to change (i.e., there was no learning) in either trial. The first two columns show the spatial rate map and autocorrelogram of the cells for these trials. As in Figures 5, 6, the mean (m) and peak (p) firing rates, and the gridness score (g) are provided on the top of each rate map and autocorrelogram, respectively. The top subpanels in the third column show the half-wave rectified differences of the spatial rate maps from the two trials, and the bottom subpanels show the membrane potential dynamics of the cells during 25 s segments through the two trials (black: before; red: during MS inactivation). Note the membrane potential threshold (see Γ in Equations 1.5 and 1.6) of 0.1 for cells to output activity is highlighted in either plot. Color coding from blue (min.) to red (max.) is used for each rate map, and from blue (−1) to red (1) for each autocorrelogram.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3814006&req=5

Figure 8: Firing of model grid cells in non-preferred positions during MS inactivation (Case 4). Panels (A) and (B) highlight the differential spatial and temporal responses of two model grid cells with the smaller and larger scales, respectively, between the baseline trial and the inactivation trial. Note for this case the model animal ran along the same realistic trajectory and the bottom-up synaptic weights from stripe cells were not allowed to change (i.e., there was no learning) in either trial. The first two columns show the spatial rate map and autocorrelogram of the cells for these trials. As in Figures 5, 6, the mean (m) and peak (p) firing rates, and the gridness score (g) are provided on the top of each rate map and autocorrelogram, respectively. The top subpanels in the third column show the half-wave rectified differences of the spatial rate maps from the two trials, and the bottom subpanels show the membrane potential dynamics of the cells during 25 s segments through the two trials (black: before; red: during MS inactivation). Note the membrane potential threshold (see Γ in Equations 1.5 and 1.6) of 0.1 for cells to output activity is highlighted in either plot. Color coding from blue (min.) to red (max.) is used for each rate map, and from blue (−1) to red (1) for each autocorrelogram.

Mentions: The lower spatial stability of model grid cells in the trial coinciding with MS inactivation, compared to the immediately prior one, was ascertained in several ways. Figure 7 confirms this result for four different criteria to include positions, or bins, across the environment in the computation of inter-trial linear correlations of spatial rate maps; namely, regarding (a) only those bins where the firing rate is greater than zero in either trial (Langston et al., 2010; Wills et al., 2010), (b) only those bins where the firing rate is greater than zero in both trials, (c) all bins without any condition (Koenig et al., 2011), and (d) only those bins that were visited by the model animal in both trials (Brandon et al., 2011). To further establish that the decrease in spatial stability is not just due to missing grid firing fields, the model animal was made to run in two trials along the same realistic trajectory and with no further online changes in the strengths of connections from stripe cells to entorhinal map cells. In addition, the second trial involved reductions in cell response rates to one-fourth of their normal values. This allowed for the focused comparisons of spatial and temporal responses of model grid cells between the active and inactive MS conditions. Figure 8 provides observations of two representative model grid cells, one from each of the two entorhinal populations. For either cell, the rectified subtraction of the spatial rate map corresponding to the former trial from that of the latter trial reveals various inconsistent, or non-preferred, positions where the cell became active owing to MS inactivation. This is also clearly apparent in the membrane potential dynamics of the cells between the two trials, with reduced overlap between above-threshold activities.


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)

Firing of model grid cells in non-preferred positions during MS inactivation (Case 4). Panels (A) and (B) highlight the differential spatial and temporal responses of two model grid cells with the smaller and larger scales, respectively, between the baseline trial and the inactivation trial. Note for this case the model animal ran along the same realistic trajectory and the bottom-up synaptic weights from stripe cells were not allowed to change (i.e., there was no learning) in either trial. The first two columns show the spatial rate map and autocorrelogram of the cells for these trials. As in Figures 5, 6, the mean (m) and peak (p) firing rates, and the gridness score (g) are provided on the top of each rate map and autocorrelogram, respectively. The top subpanels in the third column show the half-wave rectified differences of the spatial rate maps from the two trials, and the bottom subpanels show the membrane potential dynamics of the cells during 25 s segments through the two trials (black: before; red: during MS inactivation). Note the membrane potential threshold (see Γ in Equations 1.5 and 1.6) of 0.1 for cells to output activity is highlighted in either plot. Color coding from blue (min.) to red (max.) is used for each rate map, and from blue (−1) to red (1) for each autocorrelogram.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 8: Firing of model grid cells in non-preferred positions during MS inactivation (Case 4). Panels (A) and (B) highlight the differential spatial and temporal responses of two model grid cells with the smaller and larger scales, respectively, between the baseline trial and the inactivation trial. Note for this case the model animal ran along the same realistic trajectory and the bottom-up synaptic weights from stripe cells were not allowed to change (i.e., there was no learning) in either trial. The first two columns show the spatial rate map and autocorrelogram of the cells for these trials. As in Figures 5, 6, the mean (m) and peak (p) firing rates, and the gridness score (g) are provided on the top of each rate map and autocorrelogram, respectively. The top subpanels in the third column show the half-wave rectified differences of the spatial rate maps from the two trials, and the bottom subpanels show the membrane potential dynamics of the cells during 25 s segments through the two trials (black: before; red: during MS inactivation). Note the membrane potential threshold (see Γ in Equations 1.5 and 1.6) of 0.1 for cells to output activity is highlighted in either plot. Color coding from blue (min.) to red (max.) is used for each rate map, and from blue (−1) to red (1) for each autocorrelogram.
Mentions: The lower spatial stability of model grid cells in the trial coinciding with MS inactivation, compared to the immediately prior one, was ascertained in several ways. Figure 7 confirms this result for four different criteria to include positions, or bins, across the environment in the computation of inter-trial linear correlations of spatial rate maps; namely, regarding (a) only those bins where the firing rate is greater than zero in either trial (Langston et al., 2010; Wills et al., 2010), (b) only those bins where the firing rate is greater than zero in both trials, (c) all bins without any condition (Koenig et al., 2011), and (d) only those bins that were visited by the model animal in both trials (Brandon et al., 2011). To further establish that the decrease in spatial stability is not just due to missing grid firing fields, the model animal was made to run in two trials along the same realistic trajectory and with no further online changes in the strengths of connections from stripe cells to entorhinal map cells. In addition, the second trial involved reductions in cell response rates to one-fourth of their normal values. This allowed for the focused comparisons of spatial and temporal responses of model grid cells between the active and inactive MS conditions. Figure 8 provides observations of two representative model grid cells, one from each of the two entorhinal populations. For either cell, the rectified subtraction of the spatial rate map corresponding to the former trial from that of the latter trial reveals various inconsistent, or non-preferred, positions where the cell became active owing to MS inactivation. This is also clearly apparent in the membrane potential dynamics of the cells between the two trials, with reduced overlap between above-threshold activities.

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