Topography in the Bursting Dynamics of Entorhinal Neurons

Parahippocampal neurons encode task-relevant information for goal-directed navigation

A behavioral strategy crucial to survival is directed navigation to a goal, such as a food or home location. One potential neural substrate for supporting goal-directed navigation is the parahippocampus, which contains neurons that represent an animal's position, orientation, and movement through the world, and that change their firing activity to encode behaviorally relevant variables such as reward. However, little prior work on the parahippocampus has considered how neurons encode variables during goal-directed navigation in environments that dynamically change. Here, we recorded single units from rat parahippocampal cortex while subjects performed a goal-directed task. The maze dynamically changed goal-locations via a visual cue on a trial-to-trial basis, requiring subjects to use cue-location associations to receive reward. We observed a mismatch-like signal, with elevated neural activity on incorrect trials, leading to rate-remapping. The strength of this remapping correlated with task performance. Recordings during open-field foraging allowed us to functionally define navigational coding for a subset of the neurons recorded in the maze. This approach revealed that head-direction coding units remapped more than other functional-defined units. Taken together, this work thus raises the possibility that during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

T-type Ca2+ and persistent Na+ currents synergistically elevate ventral, not dorsal, entorhinal cortical stellate cell excitability

Dorsal and ventral medial entorhinal cortex (mEC) regions have distinct neural network firing patterns to differentially support functions such as spatial memory. Accordingly, mEC layer II dorsal stellate neurons are less excitable than ventral neurons. This is partly because the densities of inhibitory conductances are higher in dorsal than ventral neurons. Here, we report that T-type Ca2+ currents increase 3-fold along the dorsal-ventral axis in mEC layer II stellate neurons, with twice as much CaV3.2 mRNA in ventral mEC compared with dorsal mEC. Long depolarizing stimuli trigger T-type Ca2+ currents, which interact with persistent Na+ currents to elevate the membrane voltage and spike firing in ventral, not dorsal, neurons. T-type Ca2+ currents themselves prolong excitatory postsynaptic potentials (EPSPs) to enhance their summation and spike coupling in ventral neurons only. These findings indicate that T-type Ca2+ currents critically influence the dorsal-ventral mEC stellate neuron excitability gradient and, thereby, mEC dorsal-ventral circuit activity.

Laminar and dorsoventral organization of layer 1 interneuronal microcircuitry in superficial layers of the medial entorhinal cortex

Layer 1 (L1) interneurons (INs) participate in various brain functions by gating information flow in the neocortex, but their role in the medial entorhinal cortex (MEC) is still unknown, largely due to scant knowledge of MEC L1 microcircuitry. Using simultaneous triple-octuple whole-cell recordings and morphological reconstructions, we comprehensively depict L1IN networks in the MEC. We identify three morphologically distinct types of L1INs with characteristic electrophysiological properties. We dissect intra- and inter-laminar cell-type-specific microcircuits of L1INs, showing connectivity patterns different from those in the neocortex. Remarkably, motif analysis reveals transitive and clustered features of L1 networks, as well as over-represented trans-laminar motifs. Finally, we demonstrate the dorsoventral gradient of L1IN microcircuits, with dorsal L1 neurogliaform cells receiving fewer intra-laminar inputs but exerting more inhibition on L2 principal neurons. These results thus present a more comprehensive picture of L1IN microcircuitry, which is indispensable for deciphering the function of L1INs in the MEC.

Remapping in a recurrent neural network model of navigation and context inference

Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ('remap') in response to changing contextual factors such as environmental cues, task conditions, and behavioral states, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.

Remapping in a recurrent neural network model of navigation and context inference

Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ("remap") in response to changing contextual factors such as environmental cues, task conditions, and behavioral state, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.

Resurgent Sodium Current in Neurons of the Cerebral Cortex

In the late ’90, Dr. Indira Raman, at the time a postdoctoral fellow with Dr. Bruce Bean, at Harvard University, identified a new type of sodium current, flowing through the channels that reopens when the membrane is repolarized. This current, called “resurgent Sodium current,” was originally identified in cerebellar Purkinje neurons and has now been confirmed in around 20 different neuronal types. Since moving to Northwestern University in 1999 to establish her own research group, Dr. Raman has dedicated great efforts in identifying the mechanisms supporting the resurgent Sodium current and how its biophysical properties shape the firing of the different cell types. Her work has impacted greatly the field of cellular neurophysiology, from basic research to translation neuroscience. In fact, alterations in the resurgent sodium currents have been observed in several neuropathologies, from Huntington’s disease to epilepsy. In this Perspective we will focus on the current knowledge on the expression and function of the resurgent Sodium current in neurons of the cerebral cortex and hippocampus. We will also briefly highlight the role of Dr. Raman’s as teacher and mentor, not only for her pupils, but for the whole scientific community.

Dynamic and reversible remapping of network representations in an unchanging environment

Neurons in the medial entorhinal cortex alter their firing properties in response to environmental changes. This flexibility in neural coding is hypothesized to support navigation and memory by dividing sensory experience into unique episodes. However, it is unknown how the entorhinal circuit as a whole transitions between different representations when sensory information is not delineated into discrete contexts. Here we describe rapid and reversible transitions between multiple spatial maps of an unchanging task and environment. These remapping events were synchronized across hundreds of neurons, differentially affected navigational cell types, and correlated with changes in running speed. Despite widespread changes in spatial coding, remapping comprised a translation along a single dimension in population-level activity space, enabling simple decoding strategies. These findings provoke reconsideration of how the medial entorhinal cortex dynamically represents space and suggest a remarkable capacity of cortical circuits to rapidly and substantially reorganize their neural representations.

Microcircuits for spatial coding in the medial entorhinal cortex

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism’s spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Spike Afterpotentials Shape the In Vivo Burst Activity of Principal Cells in Medial Entorhinal Cortex

Principal neurons in rodent medial entorhinal cortex (MEC) generate high-frequency bursts during natural behavior. While in vitro studies point to potential mechanisms that could support such burst sequences, it remains unclear whether these mechanisms are effective under in vivo conditions. In this study, we focused on the membrane-potential dynamics immediately following action potentials (APs), as measured in whole-cell recordings from male mice running in virtual corridors (Domnisoru et al., 2013). These afterpotentials consisted either of a hyperpolarization, an extended ramp-like shoulder, or a depolarization reminiscent of depolarizing afterpotentials (DAPs) recorded in vitro in MEC principal neurons. Next, we correlated the afterpotentials with the cells' propensity to fire bursts. All DAP cells with known location resided in Layer II, generated bursts, and their interspike intervals (ISIs) were typically between 5 and 15 ms. The ISI distributions of Layer-II cells without DAPs peaked sharply at around 4 ms and varied only minimally across that group. This dichotomy in burst behavior is explained by cell-group-specific DAP dynamics. The same two groups of bursting neurons also emerged when we clustered extracellular spike-train autocorrelations measured in real 2D arenas (Latuske et al., 2015). Apart from slight variations in grid spacing, no difference in the spatial coding properties of the grid cells across all three groups was discernible. Layer III neurons were only sparsely bursting (SB) and had no DAPs. As various mechanisms for modulating ion-channels underlying DAPs exist, our results suggest that temporal features of MEC activity can be altered while maintaining the cells' overall spatial tuning characteristics.SIGNIFICANCE STATEMENT Depolarizing afterpotentials (DAPs) are frequently observed in principal neurons from slice preparations of rodent medial entorhinal cortex (MEC), but their functional role in vivo is unknown. Analyzing whole-cell data from mice running on virtual tracks, we show that DAPs do occur during behavior. Cells with prominent DAPs are found in Layer II; their interspike intervals (ISIs) reflect DAP time-scales. In contrast, neither the rarely bursting cells in Layer III, nor the high-frequency bursters in Layer II, have a DAP. Extracellular recordings from mice exploring real 2D arenas demonstrate that grid cells within these three groups have similar spatial coding properties. We conclude that DAPs shape the temporal response characteristics of principal neurons in MEC with little effect on spatial properties.