How Entorhinal Grid Cells May Learn Multiple Spatial Scales from a Dorsoventral Gradient of Cell Response Rates in a Self-organizing Map

Place cells in the hippocampus of higher mammals are critical for spatial navigation. Recent modeling clarifies how this may be achieved by how grid cells in the medial entorhinal cortex (MEC) input to place cells. Grid cells exhibit hexagonal grid firing patterns across space in multiple spatial scales along the MEC dorsoventral axis. Signals from grid cells of multiple scales combine adaptively to activate place cells that represent much larger spaces than grid cells. But how do grid cells learn to fire at multiple positions that form a hexagonal grid, and with spatial scales that increase along the dorsoventral axis? In vitro recordings of medial entorhinal layer II stellate cells have revealed subthreshold membrane potential oscillations (MPOs) whose temporal periods, and time constants of excitatory postsynaptic potentials (EPSPs), both increase along this axis. Slower (faster) subthreshold MPOs and slower (faster) EPSPs correlate with larger (smaller) grid spacings and field widths. A self-organizing map neural model explains how the anatomical gradient of grid spatial scales can be learned by cells that respond more slowly along the gradient to their inputs from stripe cells of multiple scales, which perform linear velocity path integration. The model cells also exhibit MPO frequencies that covary with their response rates. The gradient in intrinsic rhythmicity is thus not compelling evidence for oscillatory interference as a mechanism of grid cell firing. A response rate gradient combined with input stripe cells that have normalized receptive fields can reproduce all known spatial and temporal properties of grid cells along the MEC dorsoventral axis. This spatial gradient mechanism is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections. Spatial and temporal representations may hereby arise from homologous mechanisms, thereby embodying a mechanistic “neural relativity” that may clarify how episodic memories are learned.     

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity.     

Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons: Effect of Single Neuron Properties and Network Dynamics

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity.     

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km²) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts.     

A Spatial Map of Onset and Sustained Responses to Speech in the Human Superior Temporal Gyrus

Download video (38MB)Help with mp4 files     

Lactobacillus rhamnosus GG and Bifidobacterium bifidum TMC3115 Can Affect Development of Hippocampal Neurons Cultured In Vitro in a Strain-Dependent Manner

This study examined whether Lactobacillus rhamnosus GG (LGG) and Bifidobacterium bifidum TMC3115 (TMC3115) could morphologically or physiologically influence hippocampal neuronal development in vitro. Hippocampal neurons cultured in vitro were exposed to live or heat-inactivated LGG or TMC3115 for either 6 or 24 h. Neuronal morphological changes and drebrin (DRB) and synaptophysin (SYP) protein levels were monitored using immunofluorescence. And the levels of DRB, SYP, and brain-derived neurotrophic factor (BDNF), and cAMP-response element binding protein (CREB) mRNA were detected using RT-PCR. The BDNF, CREB, and phosphorylated-CREB (P-CREB) protein levels were detected by extraction-enzyme-linked immunosorbent assay (ELISA) or Western blot assays. Heat-inactivated LGG and TMC3115 could enhance neuron viability, DRB and SYP protein levels, and BDNF mRNA level were significantly altered after exposure to the tested bacteria with 6 h or 24 h. There were no significant differences in neuronal morphology or DRB, SYP, or CREB mRNA levels among the groups following bacterial exposure. However, following exposure of live TMC3115 for 24 h, the neuronal BDNF and P-CREB protein levels were both significantly up-regulated as detected by western blot assays. These results demonstrated that LGG and TMC3115 could affect neuronal viability, along with hippocampal synaptic and functional development, in a strain-dependent manner, which may also be closely associated with the physiological and culture conditions of each strain. Up-regulated P-CREB may be one of the underlying mechanisms by which the bacteria, especially neurons following exposure of live TMC3115 for 24 h, are able to regulate neuronal BDNF protein production.

     

Immunohistochemical Visualization of Hippocampal Neuron Activity After Spatial Learning in a Mouse Model of Neurodevelopmental Disorders

Induction of phosphorylated extracellular-regulated kinase (pERK) is a reliable molecular readout of learning-dependent neuronal activation. Here, we describe a pERK immunohistochemistry protocol to study the profile of hippocampal neuron activation following exposure to a spatial learning task in a mouse model characterized by cognitive deficits of neurodevelopmental origin. Specifically, we used pERK immunostaining to study neuronal activation following Morris water maze (MWM, a classical hippocampal-dependent learning task) in Engrailed-2 knockout (En2^-/-) mice, a model of autism spectrum disorders (ASD). As compared to wild-type (WT) controls, En2^-/- mice showed significant spatial learning deficits in the MWM. After MWM, significant differences in the number of pERK-positive neurons were detected in specific hippocampal subfields of En2^-/- mice, as compared to WT animals. Thus, our protocol can robustly detect differences in pERK-positive neurons associated to hippocampal-dependent learning impairment in a mouse model of ASD. More generally, our protocol can be applied to investigate the profile of hippocampal neuron activation in both genetic or pharmacological mouse models characterized by cognitive deficits.     

A Neurodynamical Model of Visual Attention: Feedback Enhancement of Spatial Resolution in a Hierarchical System

Human beings have the capacity to recognize objects in natural visual scenes with high efficiency despite the complexity of such scenes, which usually contain multiple objects. One possible mechanism for dealing with this problem is selective attention. Psychophysical evidence strongly suggests that selective attention can enhance the spatial resolution in the input region corresponding to the focus of attention. In this work we adopt a computational neuroscience perspective to analyze the attentional enhancement of spatial resolution in the area containing the objects of interest. We extend and apply the computational model of Deco and Schürmann (2000), which consists of several modules with feedforward and feedback interconnections describing the mutual links between different areas of the visual cortex. Each module analyses the visual input with different spatial resolution and can be thought of as a hierarchical predictor at a given level of resolution. Moreover, each hierarchical predictor has a submodule that consists of a group of neurons performing a biologically based 2D Gabor wavelet transformation at a given resolution level. The attention control decides in which local regions the spatial resolution should be enhanced in a serial fashion. In this sense, the scene is first analyzed at a coarse resolution level, and the focus of attention enhances iteratively the resolution at the location of an object until the object is identified. We propose and simulate new psychophysical experiments where the effect of the attentional enhancement of spatial resolution can be demonstrated by predicting different reaction time profiles in visual search experiments where the target and distractors are defined at different levels of resolution.     

Properties and the Cytoskeletal Control of Ca++-independent Large Conductance K+ Channels in Neonatal Rat Hippocampal Neurons

A member of the family of Ca⁺⁺-independent large conductance K⁺ channels (termed BK channels) was identified in patch clamp experiments with cultured neonatal rat hippocampal neurons. Permeation was characterized (at 5 mmol/l external, 140 mmol/l internal K⁺; 135 mmol/l external Na⁺) by a conductance of 107 pS, a ratio P_Na/P_K∼ 0.01, and outward rectification near the reversal potential. Channel activity was not voltage-dependent, could not be reduced by internal TEA or by a shift of internal pH from 7.4 to 6.8, i.e., discriminating features within the Ca⁺⁺-independent BK channel family. Cytosolic proteolysis abolished the functional state of hippocampal Ca⁺⁺-independent BK channels, in contrast to the pronase resistance of hippocampal Ca⁺⁺-activated BK channels which suggests structural dissimilarities between these related channels. Cytoskeletal alterations had an activating influence on Ca⁺⁺-independent BK channels and caused a 3–4-fold rise in P _o , but patch excision and channel isolation from the natural environment provoked the strongest increase in P _o , from 0.07 ± 0.03 to 0.73 ± 0.04. This activation process operated slowly, on a minute time scale and can be most easily explained with the loss of a membrane-associated inhibitory particle. Once activated, Ca⁺⁺-independent BK channels reacted sensitively to a Mg-ATP supplemented brain tissue extract with a P _o decline, from 0.60 ± 0.06 to 0.10 ± 0.05. Heated extracts failed to induce significant channel inhibition, providing evidence for a heat-unstable molecule with reassociates with the internal channel surface to reestablish channel inhibition. A dualistic channel control, by this membrane-associated molecule and by the cytoskeleton seems possible. Received: 16 July 1997/Revised: 3 November 1997     

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.     

Rosiglitazone Suppresses In Vitro Seizures in Hippocampal Slice by Inhibiting Presynaptic Glutamate Release in a Model of Temporal Lobe Epilepsy

Peroxisomal proliferator-activated receptor gamma (PPARγ) is a nuclear hormone receptor whose agonist, rosiglitazone has a neuroprotective effect to hippocampal neurons in pilocarpine-induced seizures. Hippocampal slice preparations treated in Mg²⁺ free medium can induce ictal and interictal-like epileptiform discharges, which is regarded as an in vitro model of N-methyl-D-aspartate (NMDA) receptor-mediated temporal lobe epilepsy (TLE). We applied rosiglitazone in hippocampal slices treated in Mg²⁺ free medium. The effects of rosiglitazone on hippocampal CA1-Schaffer collateral synaptic transmission were tested. We also examined the neuroprotective effect of rosiglitazone toward NMDA excitotoxicity on cultured hippocampal slices. Application of 10μM rosiglitazone significantly suppressed amplitude and frequency of epileptiform discharges in CA1 neurons. Pretreatment with the PPARγ antagonist GW9662 did not block the effect of rosiglitazone on suppressing discharge frequency, but reverse the effect on suppressing discharge amplitude. Application of rosiglitazone suppressed synaptic transmission in the CA1-Schaffer collateral pathway. By miniature excitatory-potential synaptic current (mEPSC) analysis, rosiglitazone significantly suppressed presynaptic neurotransmitter release. This phenomenon can be reversed by pretreating PPARγ antagonist GW9662. Also, rosiglitazone protected cultured hippocampal slices from NMDA-induced excitotoxicity. The protective effect of 10μM rosiglitazone was partially antagonized by concomitant high dose GW9662 treatment, indicating that this effect is partially mediated by PPARγ receptors. In conclusion, rosiglitazone suppressed NMDA receptor-mediated epileptiform discharges by inhibition of presynaptic neurotransmitter release. Rosiglitazone protected hippocampal slice from NMDA excitotoxicity partially by PPARγ activation. We suggest that rosiglitazone could be a potential agent to treat patients with TLE.     

Correlations and Functional Connections in a Population of Grid Cells

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern.     

Network Oscillations Drive Correlated Spiking of ON and OFF Ganglion Cells in the rd1 Mouse Model of Retinal Degeneration

Following photoreceptor degeneration, ON and OFF retinal ganglion cells (RGCs) in the rd-1/rd-1 mouse receive rhythmic synaptic input that elicits bursts of action potentials at ∼10 Hz. To characterize the properties of this activity, RGCs were targeted for paired recording and morphological classification as either ON alpha, OFF alpha or non-alpha RGCs using two-photon imaging. Identified cell types exhibited rhythmic spike activity. Cross-correlation of spike trains recorded simultaneously from pairs of RGCs revealed that activity was correlated more strongly between alpha RGCs than between alpha and non-alpha cell pairs. Bursts of action potentials in alpha RGC pairs of the same type, i.e. two ON or two OFF cells, were in phase, while bursts in dissimilar alpha cell types, i.e. an ON and an OFF RGC, were 180 degrees out of phase. This result is consistent with RGC activity being driven by an input that provides correlated excitation to ON cells and inhibition to OFF cells. A2 amacrine cells were investigated as a candidate cellular mechanism and found to display 10 Hz oscillations in membrane voltage and current that persisted in the presence of antagonists of fast synaptic transmission and were eliminated by tetrodotoxin. Results support the conclusion that the rhythmic RGC activity originates in a presynaptic network of electrically coupled cells including A2s via a Na⁺-channel dependent mechanism. Network activity drives out of phase oscillations in ON and OFF cone bipolar cells, entraining similar frequency fluctuations in RGC spike activity over an area of retina that migrates with changes in the spatial locus of the cellular oscillator.     

Imaging of Mitochondrial and Non-Mitochondrial Responses in Cultured Rat Hippocampal Neurons Exposed to Micromolar Concentrations of TMRM

Tetramethylrhodamine methyl ester (TMRM) is a fluorescent dye used to study mitochondrial function in living cells. Previously, we reported that TMRM effectively labeled mitochondria of neurons deep within mouse brain slices. Use of micromolar concentration of dye, which was required to get sufficient staining for two-photon imaging, resulted in typical fluctuations of TMRM. With prolonged exposure, we recorded additional responses in some neurons that included slow oscillations and propagating waves of fluorescence. (Note: We use the terms “fluctuation” to refer to a change in the fluorescent state of an individual mitochondrion, “oscillation” to refer to a localized change in fluorescence in the cytosol, and “wave” to refer to a change in cytosolic fluorescence that propagated within a cell. Use of these terms does not imply any underlying periodicity.) In this report we describe similar results using cultured rat hippocampal neurons. Prolonged exposure of cultures to 2.5 µM TMRM produced a spontaneous increase in fluorescence in some neurons, but not glial cells, after 45–60 minutes that was followed by slow oscillations, waves, and eventually apoptosis. Spontaneous increases in fluorescence were insensitive to high concentrations of FCCP (100 µM) and thapsigargin (10 µM) indicating that they originated, at least in part, from regions outside of mitochondria. The oscillations did not correlate with changes in intracellular Ca²⁺, but did correlate with differences in fluorescence lifetime of the dye. Fluorescence lifetime and one-photon ratiometric imaging of TMRM suggested that the spontaneous increase and subsequent oscillations were due to movement of dye between quenched (hydrophobic) and unquenched (hydrophilic) compartments. We propose that these movements may be correlates of intracellular events involved in early stages of apoptosis.