Long-term potentiation (LTP) of synaptic transmission, studied intensively in reduced brain preparations such as hippocampal brain slices, is the leading candidate for the cellular/molecular basis of learning and memory. Serious consideration of LTP as underlying information storage in the intact brain, however, requires understanding how LTP can be induced selectively at specific synaptic sites in a neural system when the mechanisms underlying LTP are regulated by other structural and functional properties of the same neural system. In the studies reported here, we tested the hypothesis that different patterns of activity within the same population of entorhinal cortical afferents could lead to a selective potentiation of spatially distinct populations of synapses across different regions of the hippocampus, including those activated multisynaptically. We focused specifically on potentiation of direct, monosynaptic entorhinal input to dentate granule cells, which expresses an NMDA receptor-dependent LTP, and on potentiation of indirect, disynaptic entorhinal input to CA3 pyramidal cells, which is transmitted by the mossy fiber projection of dentate granule cells and expresses an NMDA receptor-independent LTP. The principal findings of these experiments show that lower stimulation frequencies (10–20 Hz) of entorhinal cortical axons selectively induce LTP of mossy fiber input to CA3 transsynaptically via excitation of dentate granule cells, and that patterns of stimulation of that mimic neuronal firing in the entorhinal cortex during endogenous theta rhythm (five-impulse bursts at 200 Hz, interburst intervals of 200 msec) induce LTP both monosynaptically for input to dentate granule cells and transsynaptically for mossy fiber input to CA3.
LTP; CA3; CA1; pyramidal cell; dentate gyrus; granule cell; mossy fiber; perforant path; entorhinal cortex; transsynaptic; in vivo; learning; memory
The learning mechanism in the hippocampus has almost universally been assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of memories later. However, it is also widely known that Hebbian learning mechanisms impose significant capacity constraints, and are generally less computationally powerful than learning mechanisms that take advantage of error signals. We show that the differential phase relationships of hippocampal subfields within the overall theta rhythm enable a powerful form of error-driven learning, which results in significantly greater capacity, as shown in computer simulations. In one phase of the theta cycle, the bidirectional connectivity between CA1 and entorhinal cortex can be trained in an error-driven fashion to learn to effectively encode the cortical inputs in a compact and sparse form over CA1. In a subsequent portion of the theta cycle, the system attempts to recall an existing memory, via the pathway from entorhinal cortex to CA3 and CA1. Finally the full theta cycle completes when a strong target encoding representation of the current input is imposed onto the CA1 via direct projections from entorhinal cortex. The difference between this target encoding and the attempted recall of the same representation on CA1 constitutes an error signal that can drive the learning of CA3 to CA1 synapses. This CA3 to CA1 pathway is critical for enabling full reinstatement of recalled hippocampal memories out in cortex. Taken together, these new learning dynamics enable a much more robust, high-capacity model of hippocampal learning than was available previously under the classical Hebbian model.
We present a novel hippocampal model based on the oscillatory dynamics of the theta rhythm, which enables the network to learn much more efficiently than the Hebbian form of learning that is widely assumed in most models. Specifically, two pathways, Tri-Synaptic and Mono-Synaptic, alternate in strength during theta oscillations to provide an alternation of encoding vs. recall bias in area CA1. The difference between these two states and the unaltered cortical input representation creates an error signal, which can drive powerful error-driven learning in both Tri-Synaptic and Mono-Synaptic pathways. Furthermore, the presence of these alternating modes of network behavior (encoding vs. recall) provide an intriguing target for future work examining how prefrontal control mechanisms can manipulate the behavior of the hippocampus.
The hippocampus of the mammalian brain is important for the formation of long term memories. Hippocampal-dependent learning can be affected by a number of neurotransmitters including the activation of μ-opioid receptors (MOR). It has been shown that MOR activation can alter synaptic plasticity and network oscillations in the hippocampus, both of which are thought to be important for the encoding of information and formation of memories. One hippocampal oscillation that has been correlated with learning and memory formation is the 4-10 Hz theta rhythm. During theta rhythms, inputs to hippocampal CA1 from CA3 (Schaffer collaterals, SC) and the entorhinal cortex (perforant path) can integrate at different times within an individual theta cycle. Consequently, when excitatory inputs in the stratum lacunosum-moleculare (the temporo-ammonic pathway (TA), which includes the perforant path) are stimulated approximately one theta period before SC inputs, the TA can indirectly inhibit SC inputs. This inhibition is due to the activation of postsynaptic GABAB receptors on CA1 pyramidal neurons. Importantly, MOR activation has been shown to suppress GABAB inhibitory postsynaptic potentials in CA1 pyramidal neurons. Therefore, we examined how MOR activation affects the integration between TA inputs and SC inputs in hippocampal CA1. To do this we used voltage-sensitive dye imaging and whole cell patch clamping from acute hippocampal slices taken from young adult rats. Here we show that MOR activation has no effect on the integration between TA and SC inputs when activation of the TA precedes SC by less than one half of a theta cycle (< 75 ms). However, MOR activation completely blocked the inhibitory action of TA on SC inputs when TA stimulation occurred approximately one theta cycle before SC activation (> 150 ms). This MOR suppression of TA driven inhibition occurred in both the SC input layer of hippocampal CA1 (stratum radiatum) and the output layer of CA1 pyramidal neurons (stratum pyramidale). Thus MOR activation can have profound effects on the temporal integration between two primary excitatory pathways to hippocampal CA1 and subsequently the resultant output from CA1 pyramidal neurons. These data provide important information for understanding how acute or chronic MOR activation may affect the integration of activity within hippocampal CA1 during theta rhythm.
voltage-sensitive dye; integration; interneuron; feed forward; theta
A multimodal neuroimaging study of virtual spatial navigation extends the role of the hippocampal theta rhythm to human memory and self-directed learning.
The hippocampus is crucial for episodic or declarative memory and the theta rhythm has been implicated in mnemonic processing, but the functional contribution of theta to memory remains the subject of intense speculation. Recent evidence suggests that the hippocampus might function as a network hub for volitional learning. In contrast to human experiments, electrophysiological recordings in the hippocampus of behaving rodents are dominated by theta oscillations reflecting volitional movement, which has been linked to spatial exploration and encoding. This literature makes the surprising cross-species prediction that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. We examined the links between theta, spatial exploration, and memory encoding by designing an interactive human spatial navigation paradigm combined with multimodal neuroimaging. We used both non-invasive whole-head Magnetoencephalography (MEG) to look at theta oscillations and Functional Magnetic Resonance Imaging (fMRI) to look at brain regions associated with volitional movement and learning. We found that theta power increases during the self-initiation of virtual movement, additionally correlating with subsequent memory performance and environmental familiarity. Performance-related hippocampal theta increases were observed during a static pre-navigation retrieval phase, where planning for subsequent navigation occurred. Furthermore, periods of the task showing movement-related theta increases showed decreased fMRI activity in the parahippocampus and increased activity in the hippocampus and other brain regions that strikingly overlap with the previously observed volitional learning network (the reverse pattern was seen for stationary periods). These fMRI changes also correlated with participant's performance. Our findings suggest that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. These findings directly extend the role of the hippocampus in spatial exploration in rodents to human memory and self-directed learning.
Neural activity both within and across brain regions can oscillate in different frequency ranges (such as alpha, gamma, and theta frequencies), and these different ranges are associated with distinct functions. In behaving rodents, for example, theta rhythms (4–12 Hz) in the hippocampus are prominent during the initiation of movement and have been linked to spatial exploration. Recent evidence in humans, however, suggests that the human hippocampus is involved in guiding self-directed learning. This suggests that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. In this study, we tested whether there is a human analogue for the movement-initiation-related theta rhythm found in the rodent hippocampus by using a virtual navigation paradigm, combined with non-invasive recordings and functional imaging techniques. Our recordings showed that, indeed, theta power increases are linked to movement initiation. We also examined the relationship to memory encoding, and we found that hippocampal theta oscillations related to pre-retrieval planning predicted memory performance. Imaging results revealed that periods of the task showing movement-related theta also showed increased activity in the hippocampus, as well as other brain regions associated with self-directed learning. These findings directly extend the role of the hippocampal theta rhythm in rodent spatial exploration to human memory and self-directed learning.
Current hypothetical models of Alzheimer’s disease (AD) pathogenesis emphasize the role of beta amyloid, tau deposition, and neurodegenerative changes in the mesial temporal lobe, particularly entorhinal cortex and hippocampus. However, many individuals with clinical AD who come to autopsy also exhibit cerebrovascular disease. The relationship between AD and vascular pathology is unclear, especially whether they represent additive and independent effects on neuronal injury. We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to 1) confirm whether entorhinal cortex and hippocampal volume is associated with memory among individuals with amnestic mild cognitive impairment (MCI) who are at risk for AD; and 2) determine whether regional white matter hyperintensity (WMH) volume, a radiological marker of small vessel cerebrovascular disease, is associated with entorhinal cortex and hippocampal volume independent of putative AD biomarkers in this group.
Cognitive test scores, entorhinal cortex volume, hippocampus volume, intracranial volume, and cerebrospinal fluid-derived phosphorylated tau and Aβ1–42 protein levels were measured in 199 subjects with amnestic MCI (mean age=74.89+/−7.47). Lobar WMH volumes were derived from T1-, proton-density-, and T2-weighted MRI scans. We examined the association between entorhinal cortex volume and cognition. Next, we examined the association of tau and Aβ1–42 with entorhinal cortex volume and between lobar WMH and entorhinal cortex volume. Finally, tau, Aβ1–42, and regional WMH volumes were entered simultaneously to predict entorhinal cortex volume. We repeated the analyses with hippocampal volume instead of entorhinal cortex volume. The analyses were also repeated with the sample restricted to those MCI patients who transitioned to AD on subsequent ADNI follow-up visits (n=86).
Larger entorhinal cortex volume was associated with better memory but not with performance on a task of executive functioning. Lower levels of Aβ1–42 and higher temporal WMH volumes were associated with smaller entorhinal cortex volume. When entered simultaneously, temporal lobe WMH volume was more reliably associated with entorhinal cortex volume than was Aβ1–42. The findings were similar for hippocampus volume and when the sample was restricted to MCI patients who subsequently transitioned to AD.
The findings confirm the role of entorhinal cortex and hippocampus volume in influencing memory decline in amnestic MCI, and emphasize that even in this nominally AD prodromal condition, WMH may be influencing regional neurodegeneration.
Mild Cognitive Impairment; Alzheimer’s disease; white matter hyperintensities; beta amyloid; tau
Recent discoveries have emphasized the role of the vestibular system in cognitive processes such as memory, spatial navigation and bodily self-consciousness. A precise understanding of the vestibular pathways involved is essential to understand the consequences of vestibular diseases for cognition, as well as develop therapeutic strategies to facilitate recovery. The knowledge of the “vestibular cortical projection areas”, defined as the cortical areas activated by vestibular stimulation, has dramatically increased over the last several years from both anatomical and functional points of view. Four major pathways have been hypothesized to transmit vestibular information to the vestibular cortex: (1) the vestibulo-thalamo-cortical pathway, which probably transmits spatial information about the environment via the parietal, entorhinal and perirhinal cortices to the hippocampus and is associated with spatial representation and self-versus object motion distinctions; (2) the pathway from the dorsal tegmental nucleus via the lateral mammillary nucleus, the anterodorsal nucleus of the thalamus to the entorhinal cortex, which transmits information for estimations of head direction; (3) the pathway via the nucleus reticularis pontis oralis, the supramammillary nucleus and the medial septum to the hippocampus, which transmits information supporting hippocampal theta rhythm and memory; and (4) a possible pathway via the cerebellum, and the ventral lateral nucleus of the thalamus (perhaps to the parietal cortex), which transmits information for spatial learning. Finally a new pathway is hypothesized via the basal ganglia, potentially involved in spatial learning and spatial memory. From these pathways, progressively emerges the anatomical network of vestibular cognition.
vestibular system; neuroanatomy; cognition; hippocampus; vestibular cortex; spatial orientation; basal ganglia; theta
To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments.
Navigating robots face similar challenges to wild rodents in creating useable maps of their environments. Both must learn about their environments through experience, and in doing so face similar problems dealing with ambiguous and noisy information from their sensory inputs. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Neural recordings from navigating rats have revealed cells with grid-like spatial firing properties in the entorhinal cortex region of the rodent brain. Here we show how a robot equipped with conjunctive grid-cell-like cells can maintain multiple estimates of pose and solve a navigation task in an environment with no uniquely identifying cues. We propose that grid cells in the entorhinal cortex provide a similar ability for rodents. Robotics has learned much from biological systems. In a complementary way, in this study our understanding of neural systems is enhanced by insights from engineered solutions to a common problem faced by mobile robots and navigating animals.
Hippocampal “place cells” and the precession of their extracellularly recorded spiking during traversal of a “place field” are well-established phenomena. More recent experiments describe associated entorhinal “grid cell” firing, but to date only conceptual models have been offered to explain the potential interactions among entorhinal cortex (EC) and hippocampus. To better understand not only spatial navigation, but mechanisms of episodic and semantic memory consolidation and reconsolidation, more detailed physiological models are needed to guide confirmatory experiments. Here, we report the results of a putative entorhinal-hippocampal circuit level model that incorporates recurrent asynchronous-irregular non-linear (RAIN) dynamics, in the context of recent in vivo findings showing specific intracellular–extracellular precession disparities and place field destabilization by entorhinal lesioning. In particular, during computer-simulated rodent maze navigation, our model demonstrate asymmetric ramp-like depolarization, increased theta power, and frequency (that can explain the phase precession disparity), and a role for STDP and KAHP channels. Additionally, we propose distinct roles for two entorhinal cell populations projecting to hippocampus. Grid cell populations transiently trigger place field activity, while tonic “suppression-generating cell” populations minimize aberrant place cell activation, and limit the number of active place cells during traversal of a given field. Applied to place-cell RAIN networks, this tonic suppression explains an otherwise seemingly discordant association with overall increased firing. The findings of this circuit level model suggest in vivo and in vitro experiments that could refute or support the proposed mechanisms of place cell dynamics and modulating influences of EC.
place cell; grid cell; suppression-generating cell; theta oscillation; KAHP channels; STDP; spatial navigation and memory
The entorhinal cortex is a part of the hippocampal complex that is essential to learning and memory, and nicotine affects memory by activating nicotinic acetylcholine receptors (nAChRs) in the hippocampal complex. However, it is not clear what types of neurons in the entorhinal cortex are sensitive to nicotine, and whether they play a role in nicotine-induced memory functions. Here we have used voltage sensitive dye imaging (VSDI) methods to locate the neuronal populations responsive to nicotine in entorhino-hippocampal slices, and to clarify which nAChR subtypes are involved. In combination with patch-clamp methods, we found that a concentration of nicotine comparable to exposure during smoking depolarized neurons in layer VI of the EC (ECVI) by acting through the non-α7 subtype of nAChRs. Neurons in the subiculum (Sb; close to the deep EC layers) also contain nicotine-sensitive neurons, and it is known that Sb neurons project to the ECVI. When we recorded evoked EPSCs (eEPSCs) from ECVI neurons while stimulating the Sb near the CA1 region, a low dose of nicotine not only enhanced synaptic transmission (by increasing eEPSC amplitude), but also enhanced plasticity by converting tetanus stimulation-induced short-term potentiation (STP) to long-term potentiation (LTP); nicotine enhanced synaptic transmission and plasticity of ECVI synapses by acting on both the α7 and non-α7 subtypes of nAChRs. Our data suggest that ECVI neurons are important regulators of hippocampal function and plasticity during smoking.
Nicotinic; acetylcholine; hippocampus; interneuron; patch clamp; channel
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.
Spatial navigation is a critical competence of all higher mammals, and place cells in the hippocampus represent the large spaces in which they navigate. Recent modeling clarifies how this may occur via interactions between grid cells in the medial entorhinal cortex (MEC) and place cells. Grid cells exhibit hexagonal grid firing patterns across space and come in multiple spatial scales that increase along the dorsoventral axis of MEC. Signals from multiple scales of grid cells combine to activate place cells that represent much larger spaces than grid cells. This article shows how a gradient of cell response rates along the dorsoventral axis enables the learning of grid cells with the observed gradient of spatial scales as an animal navigates realistic trajectories. The observed gradient of grid cell membrane potential oscillation frequencies is shown to be a direct result of the gradient of response rates. This gradient mechanism for spatial learning is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections, thereby clarifying why both spatial and temporal representations are found in the entorhinal-hippocampal system.
Spike-timing-dependent synaptic plasticity (STDP) is a simple and effective learning rule for sequence learning. However, synapses being subject to STDP rules are readily influenced in noisy circumstances because synaptic conductances are modified by pre- and postsynaptic spikes elicited within a few tens of milliseconds, regardless of whether those spikes convey information or not. Noisy firing existing everywhere in the brain may induce irrelevant enhancement of synaptic connections through STDP rules and would result in uncertain memory encoding and obscure memory patterns. We will here show that the LTD windows of the STDP rules enable robust sequence learning amid background noise in cooperation with a large signal transmission delay between neurons and a theta rhythm, using a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections. The important element of the present model for robust sequence learning amid background noise is the symmetric STDP rule having LTD windows on both sides of the LTP window, in addition to the loop connections having a large signal transmission delay and the theta rhythm pacing activities of stellate cells. Above all, the LTD window in the range of positive spike-timing is important to prevent influences of noise with the progress of sequence learning.
STDP; LTD window; Noise; Sequence learning; Entorhinal cortex; Entorhinal-hippocampal loop circuitry; Large transmission delay; Theta rhythm
Despite decades of research on spatial memory, we know surprisingly little about how the brain guides navigation to goals. While some models argue that vectors are represented for navigational guidance, other models postulate that the future path is computed. Although the hippocampal formation has been implicated in processing spatial goal information, it remains unclear whether this region processes path- or vector-related information.
We report neuroimaging data collected from subjects navigating London’s Soho district; these data reveal that both the path distance and the Euclidean distance to the goal are encoded by the medial temporal lobe during navigation. While activity in the posterior hippocampus was sensitive to the distance along the path, activity in the entorhinal cortex was correlated with the Euclidean distance component of a vector to the goal. During travel periods, posterior hippocampal activity increased as the path to the goal became longer, but at decision points, activity in this region increased as the path to the goal became closer and more direct. Importantly, sensitivity to the distance was abolished in these brain areas when travel was guided by external cues.
The results indicate that the hippocampal formation contains representations of both the Euclidean distance and the path distance to goals during navigation. These findings argue that the hippocampal formation houses a flexible guidance system that changes how it represents distance to the goal depending on the fluctuating demands of navigation.
•The hippocampus represents both the path and the Euclidean distances to goals•Entorhinal activity reflects the change in the Euclidean distance when the goal is set•The posterior hippocampus represents the future path at different stages en route•Significant correlations are abolished when travel is guided by external cues
Howard et al. reveal that during the navigation of a simulated real-word environment, hippocampal and entorhinal activity is correlated with the distance to the goal. The posterior hippocampus encodes the path during travel, decision making, and detours. The entorhinal cortex encodes the distance along the vector when the goal is set.
Theta oscillations in the medial temporal lobe (MTL) of mammals are involved in various functions such as spatial navigation, sensorimotor integration, and cognitive processing. While the theta rhythm was originally assumed to originate in the medial septum, more recent studies suggest autonomous theta generation in the MTL. Although coherence between entorhinal and hippocampal theta activity has been found to influence memory formation, it remains unclear whether these two structures can generate theta independently. In this study we analyzed intracranial electroencephalographic (EEG) recordings from 22 patients with unilateral hippocampal sclerosis undergoing presurgical evaluation prior to resection of the epileptic focus. Using a wavelet-based, frequency-band-specific measure of phase synchronization, we quantified synchrony between 10 different recording sites along the longitudinal axis of the hippocampal formation in the non-epileptic brain hemisphere. We compared EEG synchrony between adjacent recording sites (i) within the entorhinal cortex, (ii) within the hippocampus, and (iii) between the hippocampus and entorhinal cortex. We observed a significant interregional gap in synchrony for the delta and theta band, indicating the existence of independent delta/theta rhythms in different subregions of the human MTL. The interaction of these rhythms could represent the temporal basis for the information processing required for mnemonic encoding and retrieval.
medial temporal lobe; intracranial EEG; oscillations; synchronization; wavelet; phase precession
Mammals navigate by integrating self-motion signals (“path integration”) and occasionally fixing on familiar environmental landmarks. The rat hippocampus is a model system of spatial representation in which place cells are thought to integrate both sensory and spatial information from entorhinal cortex. The localized firing fields of hippocampal place cells and entorhinal grid-cells demonstrate a phase relationship with the local theta (6–10 Hz) rhythm that may be a temporal signature of path integration. However, encoding self-motion in the phase of theta oscillations requires high temporal precision and is susceptible to idiothetic noise, neuronal variability, and a changing environment. We present a model based on oscillatory interference theory, previously studied in the context of grid cells, in which transient temporal synchronization among a pool of path-integrating theta oscillators produces hippocampal-like place fields. We hypothesize that a spatiotemporally extended sensory interaction with external cues modulates feedback to the theta oscillators. We implement a form of this cue-driven feedback and show that it can retrieve fixed points in the phase code of position. A single cue can smoothly reset oscillator phases to correct for both systematic errors and continuous noise in path integration. Further, simulations in which local and global cues are rotated against each other reveal a phase-code mechanism in which conflicting cue arrangements can reproduce experimentally observed distributions of “partial remapping” responses. This abstract model demonstrates that phase-code feedback can provide stability to the temporal coding of position during navigation and may contribute to the context-dependence of hippocampal spatial representations. While the anatomical substrates of these processes have not been fully characterized, our findings suggest several signatures that can be evaluated in future experiments.
navigation; path integration; temporal coding; oscillations; theta rhythm; place cells; remapping
The hippocampus is a brain region that is critical for spatial learning, context-dependent memory, and episodic memory. It receives major inputs from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). MEC neurons show much greater spatial firing than LEC neurons in a recording chamber with a single, salient landmark. The MEC cells are thought to derive their spatial tuning through path integration, which permits spatially selective firing in such a cue-deprived environment. In accordance with theories that postulate two spatial mapping systems that provide input to the hippocampus—an internal, path-integration system and an external, landmark-based system—it was possible that LEC neurons can also convey a spatial signal, but that the signal requires multiple landmarks to define locations, rather than movement integration. To test this hypothesis, neurons from the MEC and LEC were recorded as rats foraged for food in cue-rich environments. In both environments, LEC neurons showed little spatial specificity, whereas many MEC neurons showed a robust spatial signal. These data strongly support the notion that the MEC and LEC convey fundamentally different types of information to the hippocampus, in terms of their spatial firing characteristics, under various environmental and behavioral conditions.
medial entorhinal cortex; medial temporal lobe; parahippocampal; spatial orientation; hippocampus
The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units. We have been applying our methods to study of the hippocampus, a cortical brain structure that has been demonstrated, in humans and in animals, to perform the cognitive function of encoding new long-term (declarative) memories. Without their hippocampi, animals and humans retain a short-term memory (memory lasting approximately 1 min), and long-term memory for information learned prior to loss of hippocampal function. Results of more than 20 years of studies have demonstrated that both individual hippocampal neurons, and populations of hippocampal cells, e.g., the neurons comprising one of the three principal subsystems of the hippocampus, induce strong, higher order, nonlinear transformations of hippocampal inputs into hippocampal outputs. For one synaptic input or for a population of synchronously active synaptic inputs, such a transformation is represented by a sequence of action potential inputs being changed into a different sequence of action potential outputs. In other words, an incoming temporal pattern is transformed into a different, outgoing temporal pattern. For multiple, asynchronous synaptic inputs, such a transformation is represented by a spatiotemporal pattern of action potential inputs being changed into a different spatiotemporal pattern of action potential outputs. Our primary thesis is that the encoding of short-term memories into new, long-term memories represents the collective set of nonlinearities induced by the three or four principal subsystems of the hippocampus, i.e., entorhinal cortex-to-dentate gyrus, dentate gyrus-to-CA3 pyramidal cell region, CA3-to-CA1 pyramidal cell region, and CA1-to-subicular cortex. This hypothesis will be supported by studies using in vivo hippocampal multineuron recordings from animals performing memory tasks that require hippocampal function. The implications for this hypothesis will be discussed in the context of “cognitive prostheses”—neural prostheses for cortical brain regions believed to support cognitive functions, and that often are subject to damage due to stroke, epilepsy, dementia, and closed head trauma.
Cognition; hippocampus; memory; modeling; nonlinear; systems analysis
Sex differences in spatial memory function have been reported with mixed results in the literature, with some studies showing male advantages and others showing no differences. When considering estrus cycle in females, results are mixed at to whether high or low circulating estradiol results in an advantage in spatial navigation tasks. Research involving humans and rodents has demonstrated males preferentially employ Euclidean strategies and utilize geometric cues in order to spatially navigate, whereas females employ landmark strategies and cues in order to spatially navigate.
This study used the water-based snowcone maze in order to assess male and female preference for landmark or geometric cues, with specific emphasis placed on the effects of estrus cycle phase for female rat. Performance and preference for the geometric cue was examined in relation to total hippocampal and hippocampal subregions (CA1&2, CA3 and dentate gyrus) volumes and entorhinal cortex thickness in order to determine the relation between strategy and spatial performance and brain area size. The study revealed that males outperformed females overall during training trials, relied on the geometric cue when the platform was moved and showed significant correlations between entorhinal cortex thickness and spatial memory performance. No gross differences in behavioural performance was observed within females when accounting for cyclicity, and only total hippocampal volume was correlated with performance during the learning trials.
This study demonstrates the sex-specific use of cues and brain areas in a spatial learning task.
The subiculum is the major output area of the hippocampus. It is closely interconnected with the entorhinal cortex and other parahippocampal areas. In animal models of temporal lobe epilepsy (TLE) and in TLE patients it exerts increased network excitability and may crucially contribute to the propagation of limbic seizures. Using immunohistochemistry and in situ-hybridization we now investigated neuropathological changes affecting parvalbumin and calretinin containing neurons in the subiculum and other parahippocampal areas after kainic acid-induced status epilepticus. We observed prominent losses in parvalbumin containing interneurons in the subiculum and entorhinal cortex, and in the principal cell layers of the pre- and parasubiculum. Degeneration of parvalbumin-positive neurons was associated with significant precipitation of parvalbumin-immunoreactive debris 24 h after kainic acid injection. In the subiculum the superficial portion of the pyramidal cell layer was more severely affected than its deep part. In the entorhinal cortex, the deep layers were more severely affected than the superficial ones. The decrease in number of parvalbumin-positive neurons in the subiculum and entorhinal cortex correlated with the number of spontaneous seizures subsequently experienced by the rats. The loss of parvalbumin neurons thus may contribute to the development of spontaneous seizures. On the other hand, surviving parvalbumin neurons revealed markedly increased expression of parvalbumin mRNA notably in the pyramidal cell layer of the subiculum and in all layers of the entorhinal cortex. This indicates increased activity of these neurons aiming to compensate for the partial loss of this functionally important neuron population. Furthermore, calretinin-positive fibers terminating in the molecular layer of the subiculum, in sector CA1 of the hippocampus proper and in the entorhinal cortex degenerated together with their presumed perikarya in the thalamic nucleus reuniens. In addition, a significant loss of calretinin containing interneurons was observed in the subiculum. Notably, the loss in parvalbumin positive neurons in the subiculum equaled that in human TLE. It may result in marked impairment of feed-forward inhibition of the temporo-ammonic pathway and may significantly contribute to epileptogenesis. Similarly, the loss of calretinin-positive fiber tracts originating from the nucleus reuniens thalami significantly contributes to the rearrangement of neuronal circuitries in the subiculum and entorhinal cortex during epileptogenesis.
▶A subpopulation of PV neurons degenerates in subiculum and entorhinal cortex after KA seizures. ▶Surviving PV neurons exhibit increased PV mRNA expression. ▶The loss in PV neurons in subiculum and entorhinal cortex correlates to spontaneous seizures. ▶Degeneration of PV neurons in the subiculum may be related to seizure-induced loss of feed-forward inhibition. ▶CR-ir neurons in the N. reuniens thalami and their projections to the subiculum degenerate.
status epilepticus; temporal lobe epilepsy; epileptogenesis; entorhinal cortex; epilepsy models; CR, calretinin; EC, entorhinal cortex; -ir, immunoreactive; KA, kainic acid; NeuN, neuron specific nuclear protein; O-LM, oriens-lacunosum moleculare; PV, parvalbumin; ROD, relative optical densities; SE, status epilepticus; TBS, tris-buffered saline; TLE, temporal lobe epilepsy
The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.
Pyramidal neurons in the hippocampus are crucially involved in learning and memory functions, but the ways in which they contribute to the processing of sensory inputs and their internal representation remain mostly unclear. The principal neurons of the CA1 region of the hippocampus are surrounded by at least 21 different types of interneurons. This feature, together with the fact that CA1 pyramidal dendrites associate two major glutamatergic inputs arriving from the entorhinal cortex, makes it laborious to track the ‘how’ and ‘what’ of synaptic integration. The present study tries to shed light on the ‘what’, that is, the information content of the CA1 discharge pattern. Using a detailed biophysical CA1 neuron model, we show that the output of the model neuron contains spatial and temporal features of the incoming synaptic input. This information lies in the temporal pattern of the inter-spike intervals produced during the bursting activity which is induced by the temporal coincidence of the two activated synaptic streams. Our findings suggest that CA1 pyramidal neurons may be capable of capturing features of the ongoing network activity via the use of a temporal code for information transfer.
Memories are thought to be encoded as a distributed representation in the neocortex. The medial prefrontal cortex (mPFC) has been shown to support the expression of memories that initially depend on the hippocampus (HPC), yet the mechanisms by which the HPC and mPFC access the distributed representations in the neocortex are unknown. By measuring phase synchronization of local field potential (LFP) oscillations, we found that learning initiated changes in neuronal communication of the HPC and mPFC with the lateral entorhinal cortex (LEC), an area that is connected with many other neocortical regions. LFPs were recorded simultaneously from the three brain regions while rats formed an association between an auditory stimulus (CS) and eyelid stimulation (US) in a trace eyeblink conditioning paradigm, as well as during retention 1 month following learning. Over the course of learning, theta oscillations in the LEC and mPFC became strongly synchronized following presentation of the CS on trials in which rats exhibited a conditioned response (CR), and this strengthened synchronization was also observed during remote retention. In contrast, CS-evoked theta synchronization between the LEC and HPC decreased with learning. Our results suggest that communication between the LEC and mPFC are strengthened with learning whereas the communication between the LEC and HPC are concomitantly weakened, suggesting that enhanced LEC–mPFC communication may be a neuronal correlate for theoretically proposed neocortical reorganization accompanying encoding and consolidation of a memory.
consolidation; episodic memory; trace conditioning; EEG; rats
Caloric restriction by fasting has been implicated to facilitate synaptic plasticity and promote contextual learning. However, cellular and molecular mechanisms underlying the effect of fasting on memory consolidation are not completely understood. We hypothesized that fasting-induced enhancement of synaptic plasticity was mediated by the increased signaling mediated by CREB (cAMP response element binding protein), an important nuclear protein and the transcription factor that is involved in the consolidation of memories in the hippocampus. In the in vivo rat model of 18 h fasting, the expression of phosphorylated CREB (pCREB) was examined using anti-phospho-CREB (Ser133) in cardially-perfused and cryo-sectioned rat brain specimens. When compared with control animals, the hippocampus exhibited up to a twofold of increase in pCREB expression in fasted animals. The piriform cortex, the entorhinal cortex, and the cortico-amygdala transitional zone also significantly increased immunoreactivities to pCREB. In contrast, the amygdala did not show any change in the magnitude of pCREB expression in response to fasting. The arcuate nucleus in the medial hypothalamus, which was previously reported to up-regulate CREB phosphorylation during fasting of up to 48 h, was also strongly immunoreactive and provided a positive control in the present study. Our findings demonstrate a metabolic demand not only stimulates cAMP-dependent signaling cascades in the hypothalamus, but also signals to various limbic brain regions including the hippocampus by activating the CREB signaling mechanism. The hippocampus is a primary brain structure for learning and memory. It receives hypothalamic and arcuate projections directly from the fornix. The hippocampus is also situated centrally for functional interactions with other limbic cortexes by establishing reciprocal synaptic connections. We suggest that hippocampal neurons and those in the surrounding limbic cortexes are intimately involved in the metabolism-dependent plasticity, which may be essential and necessary for successful achievement of adaptive appetitive behavior.
immunohistochemistry; entorhinal cortex; amygdala; piriform cortex; hypothalamus
Episodic memory incorporates information about specific events or occasions including spatial locations and the contextual features of the environment in which the event took place. It has been modeled in rats using spontaneous exploration of novel configurations of objects, their locations, and the contexts in which they are presented. While we have a detailed understanding of how spatial location is processed in the brain relatively little is known about where the nonspatial contextual components of episodic memory are processed. Initial experiments measured c-fos expression during an object-context recognition (OCR) task to examine which networks within the brain process contextual features of an event. Increased c-fos expression was found in the lateral entorhinal cortex (LEC; a major hippocampal afferent) during OCR relative to control conditions. In a subsequent experiment it was demonstrated that rats with lesions of LEC were unable to recognize object-context associations yet showed normal object recognition and normal context recognition. These data suggest that contextual features of the environment are integrated with object identity in LEC and demonstrate that recognition of such object-context associations requires the LEC. This is consistent with the suggestion that contextual features of an event are processed in LEC and that this information is combined with spatial information from medial entorhinal cortex to form episodic memory in the hippocampus. © 2013 Wiley Periodicals, Inc.
episodic; memory; hippocampus; associative; context
Volumetric measures of mesial temporal lobe structures on magnetic resonance imaging scans recently have been explored as potential biomarkers of dementia in patients with Parkinson's disease, with investigations primarily focused on hippocampal volume. Both in vivo magnetic resonance imaging and post-mortem tissue studies in Alzheimer's disease, however, demonstrate that the entorhinal cortex is involved earlier in disease-related pathology than the hippocampus. The entorhinal cortex, a region integral in declarative memory function, projects multimodal sensory information to the hippocampus via the perforant path. In Parkinson's disease, entorhinal cortex atrophy as measured on magnetic resonance imaging, however, has received less attention compared to hippocampal atrophy.
We compared entorhinal cortex and hippocampal atrophy in 12 subjects with Parkinson's disease dementia including memory impairment, 14 Parkinson's disease subjects with normal cognition, and 14 healthy controls with normal cognition, using manual segmentation methods on magnetic resonance imaging scans.
While hippocampal volumes were similar in the two Parkinson's disease cognitive groups, entorhinal cortex volumes were substantially smaller in the demented Parkinson's disease subjects compared the cognitively normal Parkinson's disease subjects (p<0.05). In addition, normalized entorhinal cortex and hippocampal volumes for right and left hemispheres were significantly lower in the demented Parkinson's disease group compared to healthy controls.
Our findings suggest that entorhinal cortex atrophy differentiates demented and cognitively normal Parkinson's disease subjects, in contrast to hippocampal atrophy. Thus, entorhinal cortex atrophy on magnetic resonance imaging may be a potential biomarker for dementia in Parkinson's disease, particularly in the setting of memory impairment.
Parkinson's disease; cognition; magnetic resonance imaging; mesial temporal lobe; Alzheimer's disease
An important aspect of normal human memory, and one humans share with many other species, is the ability to remember the location of objects in their environment. There is by now strong evidence from the study of epileptic patients undergoing brain surgery that right temporal-lobe lesions that encroach extensively upon the hippocampal and parahippocampal gyrus impair the delayed, but not the immediate, recall of the location of objects within a random array. These findings have now been extended to a multiple-trial, spatial-array learning task; by including not only patients tested after unilateral anterior temporal lobectomy but also those with a selective left or right amygdalohippocampectomy, it has been shown that the deficits associated with right hippocampal lesions are not dependent upon conjoint damage to the lateral temporal neocortex. Furthermore, the fact that on the learning task no group differences were seen on Trial 1, at zero delay, strengthened the view that the impairment was in the maintenance and subsequent retrieval of information rather than in its initial encoding. These results left unresolved the question of whether the deficit was in the mediation of object-place associations or whether it could be reduced to a more general impairment in memory for location as such. Also left unanswered was the neuroanatomical question as to the relative contributions of the hippocampus and the parahippocampal gyrus to the performance of the experimental tasks. These questions were addressed in two blood-flow activation studies that made use of positron emission tomography (PET) and magnetic resonance imaging (MRI) and incorporated computerized versions of object-location and simple-location memory tasks. Taken together, the results point to a special contribution from the anterior part of the right parahippocampal gyrus, probably corresponding to the entorhinal cortex, to the retrieval of object-place associations, a result consonant with neurophysiological findings in non-human primates.
Recent advances in single-neuron biophysics have enhanced our understanding of information processing on the cellular level, but how the detailed properties of individual neurons give rise to large-scale behavior remains unclear. Here, we present a model of the hippocampal network based on observed biophysical properties of hippocampal and entorhinal cortical neurons. We assembled our model to simulate spatial alternation, a task that requires memory of the previous path through the environment for correct selection of the current path to a reward site. The convergence of inputs from entorhinal cortex and hippocampal region CA3 onto CA1 pyramidal cells make them potentially important for integrating information about place and temporal context on the network level. Our model shows how place and temporal context information might be combined in CA1 pyramidal neurons to give rise to splitter cells, which fire selectively based on a combination of place and temporal context. The model leads to a number of experimentally testable predictions that may lead to a better understanding of the biophysical basis of information processing in the hippocampus.
Understanding how behavior is connected to cellular and network processes is one of the most important challenges in neuroscience, and computational modeling allows one to directly formulate hypotheses regarding the interactions between these scales. We present a model of the hippocampal network, an area of the brain important for spatial navigation and episodic memory, memory of “what, when, and where.” We show how the model, which consists of neurons and connections based on biophysical properties known from experiments, can guide a virtual rat through the spatial alternation task by storing a memory of the previous path through an environment. Our model shows how neurons that fire selectively based on both the current location and past trajectory of the animal (dubbed “splitter cells”) might emerge from a newly discovered biophysical interaction in these cells. Our model is not intended to be comprehensive, but rather to contain just enough detail to achieve performance of the behavioral task. Goals of this approach are to present a scenario by which the gap between biophysics and behavior can be bridged and to provide a framework for the formulation of experimentally testable hypotheses.