Two-phase computational model training long-term memories in the entorhinal-hippocampal region

A bird's eye view of the hippocampus beyond space: Behavioral, neuroanatomical, and neuroendocrine perspectives

Although the hippocampus is one of the most-studied brain regions in mammals, research on the avian hippocampus has been more limited in scope. It is generally agreed that the hippocampus is an ancient feature of the amniote brain, and therefore homologous between the two lineages. Because birds and mammals are evolutionarily not very closely related, any shared anatomy is likely to be crucial for shared functions of their hippocampi. These functions, in turn, are likely to be essential if they have been conserved for over 300 million years. Therefore, research on the avian hippocampus can help us understand how this brain region evolved and how it has changed over evolutionary time. Further, there is a strong research foundation in birds on hippocampal-supported behaviors such as spatial navigation, food caching, and brood parasitism that scientists can build upon to better understand how hippocampal anatomy, network circuitry, endocrinology, and physiology can help control these behaviors. In this review, we summarize our current understanding of the avian hippocampus in spatial cognition as well as in regulating anxiety, approach-avoidance behavior, and stress responses. Although there are still some questions about the exact number of subdivisions in the avian hippocampus and how that might vary in different avian families, there is intriguing evidence that the avian hippocampus might have complementary functional profiles along the rostral-caudal axis similar to the dorsal-ventral axis of the rodent hippocampus, where the rostral/dorsal hippocampus is more involved in cognitive processes like spatial learning and the caudal/ventral hippocampus regulates emotional states, anxiety, and the stress response. Future research should focus on elucidating the cellular and molecular mechanisms - including endocrinological - in the avian hippocampus that underlie behaviors such as spatial navigation, spatial memory, and anxiety-related behaviors, and in so doing, resolve outstanding questions about avian hippocampal function and organization.

Hippocampus shapes cortical sensory output and novelty coding through a direct feedback circuit

To extract behaviorally relevant information from our surroundings, our brains constantly integrate and compare incoming sensory information with those stored as memories. Cortico-hippocampal interactions could mediate such interplay between sensory processing and memory recall1-4 but this remains to be demonstrated. Recent work parsing entorhinal cortex-to-hippocampus circuitry show its role in episodic memory formation5-7 and spatial navigation8. However, the organization and function of the hippocampus-to-cortex back-projection circuit remains uncharted. We combined circuit mapping, physiology and behavior with optogenetic manipulations, and computational modeling to reveal how hippocampal feedback modulates cortical sensory activity and behavioral output. Here we show a new direct hippocampal projection to entorhinal cortex layer 2/3, the very layer that projects multisensory input to the hippocampus. Our finding challenges the canonical cortico-hippocampal circuit model where hippocampal feedback only reaches entorhinal cortex layer 2/3 indirectly via layer 5. This direct hippocampal input integrates with cortical sensory inputs in layer 2/3 neurons to drive their plasticity and spike output, and provides an important novelty signal during behavior for coding objects and their locations. Through the sensory-memory feedback loop, hippocampus can update real-time cortical sensory processing, efficiently and iteratively, thereby imparting the salient context for adaptive learned behaviors with new experiences.

Action-driven remapping of hippocampal neuronal populations in jumping rats

The current dominant view of the hippocampus is that it is a navigation "device" guided by environmental inputs. Yet, a critical aspect of navigation is a sequence of planned, coordinated actions. We examined the role of action in the neuronal organization of the hippocampus by training rats to jump a gap on a linear track. Recording local field potentials and ensembles of single units in the hippocampus, we found that jumping produced a stereotypic behavior associated with consistent electrophysiological patterns, including phase reset of theta oscillations, predictable global firing-rate changes, and population vector shifts of hippocampal neurons. A subset of neurons ("jump cells") were systematically affected by the gap but only in one direction of travel. Novel place fields emerged and others were either boosted or attenuated by jumping, yet the theta spike phase versus animal position relationship remained unaltered. Thus, jumping involves an action plan for the animal to traverse the same route as without jumping, which is faithfully tracked by hippocampal neuronal activity.

Hypnagogic Frontal EEG Bursts in Children: Epileptic or Not?

PURPOSE

Various EEG patterns emerge in drowsiness. Intermittent bilateral midfrontal slowing (BFS) and hypnogogic frontal predominant sharply contoured waveforms (HFSC), maximal at (Fz, F3-4, and Fp1-2), are often encountered. These do not meet the criteria for epileptiform discharges. The study objective was to determine the clinical significance of BFS and HFSC.

METHODS

Clinical information of children with BFS (n = 49) and HFSC (n = 99) was compared with control subjects with generalized spike-wave (GSW) discharges (n = 102) and normal EEGs (n = 100).

RESULTS

HFSC was present in younger children (mean age was 3.5 ± 3.6 years), whereas BFS was present in older children (mean 12.9 ± 4.8 years). Seizures occurred in the normal EEG, BFS, HFSC, and GSW groups, respectively, as follows: 22 (22%), 15 (31%), 42 (43%), and 100 (98%) patients, whereas epilepsy occurred in 17 (17%), 10 (20%), 35 (35%), and 95 (93%) patients. The GSW group had more seizures and epilepsy than the other groups (P < 0.001), but the HFSC group also had more seizures (P < 0.001) and epilepsy (P < 0.003) than the normal EEG group. Seizures and neurodevelopmental and psychiatric comorbidities were similar between the BFS and normal EEG groups. Notably, the HFSC group had more developmental delay than the normal EEG group [33 (33%) versus 18 (18%), P < 0.009] but were similar to the GSW group 22 (22%).

CONCLUSIONS

Bilateral midfrontal slowing and HFSC have had unclear significance. Our results suggest that HFSC may be a marker of increased risk of seizure, epilepsy, and developmental delay as compared to children with normal EEGs and has similar risk of developmental delay to those with GSW.

Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus

Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training ANN using error backpropagation has created the current revolution in artificial intelligence, raising the question of whether the epistemic autonomy displayed in biological cognition can be achieved with error backpropagation-based learning. We present evidence suggesting that the entorhinal-hippocampal complex combines epistemic autonomy with error backpropagation. Specifically, we propose that the hippocampus minimizes the error between its input and output signals through a modulatory counter-current inhibitory network. We further discuss the computational emulation of this principle and analyze it in the context of autonomous cognitive systems.

The contributions of entorhinal cortex and hippocampus to error driven learning

Computational models proposed that the medial temporal lobe (MTL) contributes importantly to error-driven learning, though little direct in-vivo evidence for this hypothesis exists. To test this, we recorded in the entorhinal cortex (EC) and hippocampus (HPC) as macaques performed an associative learning task using an error-driven learning strategy, defined as better performance after error relative to correct trials. Error-detection signals were more prominent in the EC relative to HPC. Early in learning hippocampal but not EC neurons signaled error-driven learning by increasing their population stimulus-selectivity following error trials. This same pattern was not seen in another task where error-driven learning was not used. After learning, different populations of cells in both the EC and HPC signaled long-term memory of newly learned associations with enhanced stimulus-selective responses. These results suggest prominent but differential contributions of EC and HPC to learning from errors and a particularly important role of the EC in error-detection.

Ku et al. recorded in the entorhinal cortex (EC) and hippocampus (HPC) of macaques during associative learning tasks in order to test the computational model prediction that they contribute to error-driven learning. They demonstrate that the EC and HPC have prominent but differential contributions to learning from errors, with the EC having a particularly prominent role in error-detection.

Region-specific Effects of Early-life Status Epilepticus on the Adult Hippocampal CA3 - Medial Entorhinal Cortex Circuitry In vitro: Focus on Interictal Spikes and Concurrent High-frequency Oscillations

Convulsive status epilepticus (SE) in immature life is often associated with lasting neurobiological changes. We provoked SE by pentylenetetrazole in postnatal day 20 rat pups and examined communication modalities between the temporal hippocampus and medial entorhinal cortex (mEC) in vitro. After a minimum of 40 days post-SE, we prepared combined temporal hippocampal - medial entorhinal cortex (mEC) slices from conditioned (SE) and naïve (N) adult rats and recorded 4-aminopyridine-induced spontaneous epileptiform interictal-like discharges (IED) simultaneously from CA3 and mEC layer V-VI. We analyzed IED frequency and high frequency oscillations (HFOs) in intact slices and after surgical separation of hippocampus from mEC, by two successive incisions (Schaffer collateral cut, Parasubiculum cut). In all slices, IED frequency was higher in CA3 vs mEC (5N, 4SE) and Raster plots indicated no temporal coincidence between them either in intact or in CA1-cut slices (4N, 4SE). IED frequency was significantly higher in SE mEC, but similar in SE and N CA3, independently of connectivity state. Ripples (R) and Fast Ripples (FR) coincided with IEDs and their power differed between SE and N intact slices (22N, 12SE), both in CA3 and mEC. CA3 FR/R ratios were higher in the absence of mEC (14N, 8SE). Moreover, SE (vs N) slices showed significantly higher FR/R ratios independently of the presence of mEC. Taken together, these findings suggest lasting effects of immature SE in network dynamics governing hippocampal-entorhinal communication which may impact adult cognitive, behavioral, and/or seizure threshold sequalae.

Entorhinal mismatch: A model of self-supervised learning in the hippocampus

The hippocampal formation displays a wide range of physiological responses to different spatial manipulations of the environment. However, very few attempts have been made to identify core computational principles underlying those hippocampal responses. Here, we capitalize on the observation that the entorhinal-hippocampal complex (EHC) forms a closed loop and projects inhibitory signals "countercurrent" to the trisynaptic pathway to build a self-supervised model that learns to reconstruct its own inputs by error backpropagation. The EHC is then abstracted as an autoencoder, with the hidden layers acting as an information bottleneck. With the inputs mimicking the firing activity of lateral and medial entorhinal cells, our model is shown to generate place cells and to respond to environmental manipulations as observed in rodent experiments. Altogether, we propose that the hippocampus builds conjunctive compressed representations of the environment by learning to reconstruct its own entorhinal inputs via gradient descent.

The Autism Palette: Combinations of Impairments Explain the Heterogeneity in ASD

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric condition traditionally defined by core symptoms in social behavior, speech/communication, repetitive behavior, and restricted interests. Beyond the core symptoms, autism has strong association with other disorders such as intellectual disability (ID), epilepsy, schizophrenia among many others. This paper outlines a theory of ASD with capacity to connect heterogeneous "core" symptoms, medical and psychiatric comorbidities as well as other etiological theories of autism in a unifying cognitive framework rooted in neuroscience and genetics. Cognition is embedded into an ever-developing structure modified by experiences, including the outcomes of environment influencing behaviors. The key constraint of cognition is that the brain can handle only 7±2 relevant variables at a time, whereas sensory variables, i.e., the number of sensory neurons is orders of magnitude larger. As a result, (a) the extraction, (b) the encoding, and (c) the capability for the efficient cognitive manipulation of the relevant variables, and (d) the compensatory mechanisms that counteract computational delays of the distributed components are critical. We outline our theoretical model to describe a Cartesian Factor (CF) forming, autoencoder-like cognitive mechanism which breaks combinatorial explosion and is accelerated by internal reinforcing machineries and discuss the neural processes that support CF formation. Impairments in any of these aspects may disrupt learning, cognitive manipulation, decisions on interactions, and execution of decisions. We suggest that social interactions are the most susceptible to combinations of diverse small impairments and can be spoiled in many ways that pile up. Comorbidity is experienced, if any of the many potential impairments is relatively strong. We consider component spoiling impairments as the basic colors of autism, whereas the combinations of individual impairments make the palette of autism. We put forth arguments on the possibility of dissociating the different main elements of the impairments that can appear together. For example, impairments of generalization (domain general learning) and impairments of dealing with many variable problems, such as social situations may appear independently and may mutually enhance their impacts. We also consider mechanisms that may lead to protection.

Simulations reveal how M-currents and memory-based inputs from CA3 enable single neuron mismatch detection for EC3 inputs to the CA1 subfield of hippocampus

Significant evidence has accumulated to support the hypothesis that hippocampal region CA1 operates as an associative mismatch detector (e.g., Hasselmo ME, Schnell E, Barkai E. J Neurosci 15: 5249-5262, 1995; Duncan K, Curtis C, Davachi L. J Neurosci 29: 131-139, 2009; Kumaran D, Maguire EA. J Neurosci 27: 8517-8524, 2007; Lisman JE, Grace AA. Neuron 46: 703-713, 2005; Lisman JE, Otmakhova NA. Hippocampus 11: 551-568 2001; Lörincz A, Buzsáki G. Ann N Y Acad Sci 911: 83-111, 2000; Meeter M, Murre JMJ, Talamini LM. Hippocampus 14: 722-741, 2004; Schiffer AM, Ahlheim C, Wurm MF, Schubotz RI. PLoS One 7: e36445, 2012; Vinogradova OS. Hippocampus 11: 578-598 2001). CA1 compares predictive synaptic signals from CA3 with synaptic signals from EC3, which reflect actual sensory inputs. The new CA1 pyramidal model presented here shows that the distal-proximal segregation of synaptic inputs from EC3 versus CA3, along with other biophysical features, enable such pyramids to serve as comparators that switch output encoding from a brief burst, for a match, to prolonged tonic spiking, for a mismatch. By including often-overlooked features of CA1 pyramidal neurons, this new model allows simulation of pharmacological effects that can eliminate either the match (phasic mode) response or the mismatch (tonic mode) response. These simulations reveal that dysfunctions can arise from either too much or too little ACh stimulation of the muscarinic receptors that control KCNQ channels. Additionally, a dysfunction caused by administration of an N-methyl-d-aspartate antagonist could be rescued by simultaneous administration of a KCNQ channel agonist, such as retigabine.NEW & NOTEWORTHY Hippocampal region CA1 operates as an associative mismatch detector, comparing predictive signals from CA3 with signals from EC3 reflecting sensory inputs. This new CA1 pyramidal model shows that biophysical features enable these comparators to switch output between brief bursts for matches and tonic spiking for mismatches. This suggests that cognitive learning models (e.g., predictive coding) may require much less match/mismatch circuitry than commonly assumed. Additional simulations illuminate deficits seen in psychiatric disorders and drug-induced states.

Primate hippocampus size and organization are predicted by sociality but not diet

The hippocampus is well known for its roles in spatial navigation and memory, but it is organized into regions that have different connections and functional specializations. Notably, the region CA2 has a role in social and not spatial cognition, as is the case for the regions CA1 and CA3 that surround it. Here, we investigated the evolution of the hippocampus in terms of its size and organization in relation to the evolution of social and ecological variables in primates, namely home range, diet and different measures of group size. We found that the volumes within the whole cornu ammonis coevolve with group size, while only the volume of CA1 and subiculum can also be predicted by home range. On the other hand, diet, expressed as a shift from folivory towards frugivory, was shown to not be related to hippocampal volume. Interestingly, CA2 was shown to exhibit phylogenetic signal only against certain measures of group size, but not with ecological factors. We also found that sex differences in the hippocampus are related to body size sex dimorphism. This is in line with reports of sex differences in hippocampal volume in non-primates that are related to social structure and sex differences in behaviour. Our findings support the notion that in primates, the hippocampus is a mosaic structure evolving in line with social pressures, where certain subsections evolve in line with spatial ability too.

Increased neuronal signatures of targeted memory reactivation during slow-wave up states

It is assumed that slow oscillatory up-states represent crucial time windows for memory reactivation and consolidation during sleep. We tested this assumption by utilizing closed-loop targeted memory reactivation: Participants were re-exposed to prior learned foreign vocabulary during up- and down-states of slow oscillations. While presenting memory cues during slow oscillatory up-states improved recall performance, down-state cueing did not result in a clear behavioral benefit. Still, no robust behavioral benefit of up- as compared to down-state cueing was observable. At the electrophysiological level however, successful memory reactivation during up-states was associated with a characteristic power increase in the theta and sleep spindle band. No oscillatory changes were observable for down-state cues. Our findings provide experimental support for the assumption that slow oscillatory up-states may represent privileged time windows for memory reactivation, while the interplay of slow oscillations, theta and sleep spindle activity promotes successful memory consolidation during sleep.

Linking major depression and the neural substrates of associative processing

It has been proposed that mood correlates with the breadth of associative thinking. Here we set this hypothesis to the test in healthy and depressed individuals. Generating contextual associations engages a network of cortical regions including the parahippocampal cortex (PHC), retrosplenial complex, and medial prefrontal cortex. The link between mood, associative processing, and its underlying cortical infrastructure provides a promising avenue for elucidating the mechanisms underlying the cognitive impairments in major depressive disorder (MDD). The participants included 15 nonmedicated individuals with acute major depressive episodes and 15 healthy matched controls. In an fMRI experiment, participants viewed images of objects that were either strongly or weakly associated with a specific context (e.g., a beach chair vs. a water bottle) while rating the commonality of each object. Analyses were performed to examine the brain activation and structural differences between the groups. Consistent with our hypothesis, controls showed greater activation of the contextual associations network than did depressed participants. In addition, PHC structural volume was correlated with ruminative tendencies, and the volumes of the hippocampal subfields were significantly smaller in depressed participants. Surprisingly, depressed participants showed increased activity in the entorhinal cortex (ERC), as compared with controls. We integrated these findings within a mechanistic account linking mood and associative thinking and suggest directions for the future.

Semi-Supervised Learning of Cartesian Factors: A Top-Down Model of the Entorhinal Hippocampal Complex

The existence of place cells (PCs), grid cells (GCs), border cells (BCs), and head direction cells (HCs) as well as the dependencies between them have been enigmatic. We make an effort to explain their nature by introducing the concept of Cartesian Factors. These factors have specific properties: (i) they assume and complement each other, like direction and position and (ii) they have localized discrete representations with predictive attractors enabling implicit metric-like computations. In our model, HCs make the distributed and local representation of direction. Predictive attractor dynamics on that network forms the Cartesian Factor "direction." We embed these HCs and idiothetic visual information into a semi-supervised sparse autoencoding comparator structure that compresses its inputs and learns PCs, the distributed local and direction independent (allothetic) representation of the Cartesian Factor of global space. We use a supervised, information compressing predictive algorithm and form direction sensitive (oriented) GCs from the learned PCs by means of an attractor-like algorithm. Since the algorithm can continue the grid structure beyond the region of the PCs, i.e., beyond its learning domain, thus the GCs and the PCs together form our metric-like Cartesian Factors of space. We also stipulate that the same algorithm can produce BCs. Our algorithm applies (a) a bag representation that models the "what system" and (b) magnitude ordered place cell activities that model either the integrate-and-fire mechanism, or theta phase precession, or both. We relate the components of the algorithm to the entorhinal-hippocampal complex and to its working. The algorithm requires both spatial and lifetime sparsification that may gain support from the two-stage memory formation of this complex.

Brain Food at High Altitude

Scenic view at high altitude is a pleasure to the eyes, but it has some shortcoming effects as well. High altitude can be divided into different categories, i.e., high altitude (3000-5000 ft), very high altitude (5000-8000 ft), and extreme altitude (above 8000 ft). Much of the population resides at high altitude, and others go there for tourism. Military personnel are also posted there to defend boundaries. As we ascent to high altitude, partial pressure of oxygen reduces, whereas concentration remains the same; this reduces the availability of oxygen to different body parts. This pathophysiological condition is known as hypobaric hypoxia (HH) which leads to oxidative stress and further causes cognitive dysfunction in some cases. Hypoxia causes neurodegeneration in different brain regions; however, the hippocampus is found to be more prone in comparison to other brain regions. As the hippocampus is affected most, therefore, spatial memory is impaired most during such condition. This chapter will give a brief review of the damaging effect of high altitude on cognition and also throw light on possible herbal interventions at high altitude, which can improve cognitive performance as well as provide protection against the deteriorating effect of hypobaric hypoxia at high altitude.

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

Human neuroimaging studies on the hippocampal CA3 region - integrating evidence for pattern separation and completion

Human functional magnetic resonance imaging (fMRI) studies have long investigated the hippocampus without differentiating between its subfields, even though theoretical models and rodent studies suggest that subfields support different and potentially even opposite functions. The CA3 region of the hippocampus has been ascribed a pivotal role both in initially forming associations during encoding and in reconstructing a memory representation based on partial cues during retrieval. These functions have been related to pattern separation and pattern completion, respectively. In recent years, studies using high-resolution fMRI in humans have begun to separate different hippocampal subregions and identify the role of the CA3 subregion relative to the other subregions. However, some of these findings have been inconsistent with theoretical models and findings from electrophysiology. In this review, we describe selected recent studies and highlight how their results might help to define different processes and functions that are presumably carried out by the CA3 region, in particular regarding the seemingly opposing functions of pattern separation and pattern completion. We also describe how these subfield-specific processes are related to behavioral, functional and structural alterations in patients with mild cognitive impairment and Alzheimer’s disease. We conclude with discussing limitations of functional imaging and briefly outline possible future developments of the field.

Forward and backward inference in spatial cognition

This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

The endocannabinoid 2-arachidonoylglycerol negatively regulates habituation by suppressing excitatory recurrent network activity and reducing long-term potentiation in the dentate gyrus

Endocannabinoids are known to mediate retrograde suppression of synaptic transmission, modulate synaptic plasticity, and influence learning and memory. The 2-arachidonoylglycerol (2-AG) produced by diacylglycerol lipase α (DGLα) is regarded as the major endocannabinoid that causes retrograde synaptic suppression. To determine how 2-AG signaling influences learning and memory, we subjected DGLα knock-out mice to two learning tasks. We tested the mice using habituation and odor-guided transverse patterning tasks that are known to involve the dentate gyrus and the CA1, respectively, of the hippocampus. We found that DGLα knock-out mice showed significantly faster habituation to an odor and a new environment than wild-type littermates with normal performance in the transverse patterning task. In freely moving animals, long-term potentiation (LTP) induced by theta burst stimulation was significantly larger at perforant path-granule cell synapses in the dentate gyrus of DGLα knock-out mice. Importantly, prior induction of synaptic potentiation at this synapse caused a significant retardation of habituation in DGLα knock-out but not in wild-type littermates. The excitability of granule cells became higher in DGLα knock-out mice after they generated action potentials. Since no differences were found in intrinsic membrane properties and responses to odor stimuli in granule cells, the elevated excitability is considered to result from enhanced activity of an excitatory recurrent network composed of granule cells and mossy cells. These results suggest that retrograde 2-AG signaling negatively regulates habituation by suppressing excitatory recurrent network activity and reducing LTP in the dentate gyrus.

Long-term results of enriched environment and erythropoietin after hypobaric hypoxia in rats

After global cerebral hypoxia, many patients are severely disabled even after intensive neurorehabilitation. Secondary mechanisms of brain injury as a result of biochemical and physiological events occur within a period of hours to months, and provide a window of opportunity for therapeutic intervention. Erythropoietin (EPO) has been shown to be neuroprotective in the brain subjected to a variety of injuries. Fifty-nine 3-month-old male Wistar rats were randomly distributed to experimental groups with respect to the housing (enriched environment - EE, standard housing - SH), to hypoxia exposure, and to EPO treatment. An acute mountain sickness model was used as a hypobaric hypoxia simulating an altitude of 8000 m. One half of the animals received erythropoietin injections, while the others were injected saline. Spatial memory was tested in a Morris water maze (MWM). The escape latency and the path length were measured. Better spatial learning in MWM was only seen in the group that received erythropoietin together with enriched environment. EPO administration itself had no influence on spatial memory. The results were very similar for both latencies and path lengths. These results support the idea that after brain injuries, the recovery can be potentiated by EPO administration combined with neurorehabilitation.

Mossy cell dendritic structure quantified and compared with other hippocampal neurons labeled in rats in vivo

Mossy cells are likely to contribute to normal hippocampal function and to the pathogenesis of neurologic disorders that involve the hippocampus, including epilepsy. Mossy cells are the least well-characterized excitatory neurons in the hippocampus. Their somatic and dendritic morphology has been described qualitatively but not quantitatively. In the present study rat mossy cells were labeled intracellularly with biocytin in vivo. Somatic and dendritic structure was reconstructed three-dimensionally. For comparison, granule cells, CA3 pyramidal cells, and CA1 pyramidal cells were labeled and analyzed using the same approach. Among the four types of hippocampal neurons, granule cells had the smallest somata, fewest primary dendrites and dendritic branches, and shortest total dendritic length. CA1 pyramidal cells had the most dendritic branches and longest total dendritic length. Mossy cells and CA3 pyramidal cells both had large somata and similar total dendritic lengths. However, mossy cell dendrites branched less than CA3 pyramidal cells, especially close to the soma. These findings suggest that mossy cells have dendritic features that are not identical to any other type of hippocampal neuron. Therefore, electrotonic properties that depend on soma-dendritic structure are likely to be distinct in mossy cells compared to other neurons.

Entorhinal Cortex Volume in Antipsychotic-naïve Schizophrenia

BACKGROUND

Entorhinal cortex (ERC), a multimodal sensory relay station for the hippocampus, is critically involved in learning, emotion, and novelty detection. One of the pathogenetic mechanistic bases in schizophrenia is proposed to involve aberrant information processing in the ERC. Several studies have looked at cytoarchitectural and morphometric changes in the ERC, but results have been inconsistent possibly due to the potential confounding effects of antipsychotic treatment.

MATERIALS AND METHODS

In this study, we have examined the entorhinal cortex volume in antipsychotic-naïve schizophrenia patients (n=40; M:F=22:18) in comparison with age, sex, and handedness, matched (as a group) with healthy subjects (n=42; M:F=25:17) using a valid method. 3-Tesla MR images with 1-mm sections were used and the data was analyzed using the SPSS software.

RESULTS

Female schizophrenia patients (1.25±0.22 mL) showed significant volume deficit in the right ERC in comparison with female healthy controls (1.45±0.34 mL) (F=4.9; P=0.03), after controlling for the potential confounding effects of intracranial volume. However, male patients did not differ from male controls. The left ERC volume did not differ between patients and controls.

CONCLUSIONS

Consistent with the findings of a few earlier studies we found a reduction in the right ERC volume in patients. However, this was limited to women. Contextually, our study finding supports the role for ERC deficit in schizophrenia pathogenesis - perhaps mediated through aberrant novelty detection. Sex-differential observation of ERC volume deficit in schizophrenia needs further studies.

Pattern separation in the dentate gyrus: a role for the CA3 backprojection

Many theories of hippocampal function assume that area CA3 of hippocampus is capable of performing rapid pattern storage, as well as pattern completion when a partial version of a familiar pattern is presented, and that the dentate gyrus (DG) is a preprocessor that performs pattern separation, facilitating storage and recall in CA3. The latter assumption derives partly from the anatomical and physiological properties of DG. However, the major output of DG is from a large number of DG granule cells to a smaller number of CA3 pyramidal cells, which potentially negates the pattern separation performed in the DG. Here, we consider a simple CA3 network model, and consider how it might interact with a previously developed computational model of the DG. The resulting "standard" DG-CA3 model performs pattern storage and completion well, given a small set of sparse, randomly derived patterns representing entorhinal input to the DG and CA3. However, under many circumstances, the pattern separation achieved in the DG is not as robust in CA3, resulting in a low storage capacity for CA3, compared to previous mathematical estimates of the storage capacity for an autoassociative network of this size. We also examine an often-overlooked aspect of hippocampal anatomy that might increase functionality in the combined DG-CA3 model. Specifically, axon collaterals of CA3 pyramidal cells project "back" to the DG ("backprojections"), exerting inhibitory effects on granule cells that could potentially ensure that different subpopulations of granule cells are recruited to respond to similar patterns. In the model, addition of such backprojections improves both pattern separation and storage capacity. We also show that the DG-CA3 model with backprojections provides a better fit to empirical data than a model without backprojections. Therefore, we hypothesize that CA3 backprojections might play an important role in hippocampal function.

Greater running speeds result in altered hippocampal phase sequence dynamics

Hebb (1949) described a "phase sequence" to be the sequential activation of sets of cell assemblies. Within the hippocampus, cell assemblies have been described as groups of coactive neurons whose place fields overlap. Membership of assemblies in a phase sequence changes systematically as a rat travels through an environment, serving to accelerate the temporal order that place fields are encountered during a single theta cycle. This sweeping forward of network activity ("look ahead"), results in locations in front of the animal being transiently represented. In this experiment, a population vector-based reconstruction method was used to capture the look ahead and reveals that the composition of the phase sequence changes with velocity, such that more cell assemblies are active within a theta cycle at higher running speeds. These results are consistent with hypotheses suggesting that hippocampal networks generate short time scale predictions of future events to optimize behavior.

Evidence for area CA1 as a match/mismatch detector: a high-resolution fMRI study of the human hippocampus

The hippocampus is proposed to switch between memory encoding and retrieval by continually computing the overlap between what is expected and what is encountered. Central to this hypothesis is that area CA1 performs this calculation. However, empirical evidence for this is lacking. To test the theoretical role of area CA1 in match/mismatch detection, we had subjects study complex stimuli and then, during high-resolution fMRI scanning, make memory judgments about probes that either matched or mismatched expectations. More than any other hippocampal subfield, area CA1 displayed responses consistent with a match/mismatch detector. Specifically, the responses in area CA1 tracked the total number of changes present in the probe. Additionally, area CA1 was sensitive to both behaviorally relevant and irrelevant changes, a key feature of an automatic comparator. These results are consistent with, and provide the first evidence in humans for, the theoretically important role of area CA1 as a match/mismatch detector.

Spike-timing-dependent plasticity in hippocampal CA3 neurons

Synaptic plasticity of different inputs converging onto CA3 pyramidal neurons is central to theories of hippocampal function. The mossy fibre (MF) input to these neurons is thought to exhibit plasticity that is in nearly all aspects fundamentally different from plasticity in other brain regions: in particular, when induced by high frequency presynaptic stimulation, plasticity at these synapses is independent of NMDA receptor (NMDAR) activation and presynaptically expressed. Here, we show that different stimulation protocols that depend on the close timing of MF activity and postsynaptic spikes induce bidirectional plasticity in CA3 neurons in 3-week-old rats. Long-term potentiation (LTP) is observed when an excitatory postsynaptic potential (EPSP), evoked by MF stimulation, precedes a single postsynaptic action potential (AP) or a brief AP burst by 10 ms. Instead, timing-dependent long-term depression (LTD) requires the pairing of a single AP to an EPSP with a delay of 30 ms. The pairing of APs to synaptic activity is required for plasticity induction, since the application of unpaired APs or EPSPs did not alter synaptic strength. Furthermore, our results demonstrate that both timing-dependent LTP and LTD critically depend on the activation of NMDARs. Specifically blocking postsynaptic NMDARs prevents plasticity, demonstrating that NMDARs important to spike-timing-dependent plasticity in CA3 neurons are required at postsynaptic sites. In summary, this study shows that the close timing of APs to MF excitatory synaptic input can alter synaptic efficacy in CA3 neurons in a bidirectional manner.

Acetylcholinesterase inhibitors enhance cognitive functions in rats following hypobaric hypoxia

Hypobaric hypoxia (HBH) can produce neuropsychological disorders such as insomnia, dizziness, memory deficiencies, headache and nausea. It is well known that exposure to HBH cause alterations of neurotransmitters and cognitive impairment in terms of learning and memory. But the mechanisms are poorly understood. The present study aimed to investigate the cholinergic system alterations associated with simulated HBH induced cognitive impairment. Male Sprague-Dawley rats were exposed to HBH equivalent to 6100 m for 7 days in a simulation chamber. The cognitive performance was assessed using Morris Water Maze (MWM) task. Cholinergic markers like acetylcholine (ACh) and acetylcholinesterase (AChE) were evaluated in hippocampus and cortex of rats. Neuronal damage was also studied through morphological changes. Exposure to HBH led to impairment in relearning ability and memory retrieval and it was accompanied by decrease in ACh level and increase in AChE and led to morphological damage. Administration of AChE inhibitor (AChEI), physostigmine (PHY) and galantamine (GAL) to rats during HBH exposure resulted in amelioration of the deleterious effects induced by HBH. The AChEIs were able to improve the cholinergic activity by restoring the level of ACh by blocking the AChE activity. In addition, the AChEIs also prevented neurodegeneration by reducing the AChE level in cortical and hippocampal neurons.

A role for sleep in brain plasticity

The idea that sleep might be involved in brain plasticity has been investigated for many years through a large number of animal and human studies, but evidence remains fragmentary. Large amounts of sleep in early life suggest that sleep may play a role in brain maturation. In particular, the influence of sleep in developing the visual system has been highlighted. The current data suggest that both Rapid Eye Movement (REM) and non-REM sleep states would be important for brain development. Such findings stress the need for optimal paediatric sleep management. In the adult brain, the role of sleep in learning and memory is emphasized by studies at behavioural, systems, cellular and molecular levels. First, sleep amounts are reported to increase following a learning task and sleep deprivation impairs task acquisition and consolidation. At the systems level, neurophysiological studies suggest possible mechanisms for the consolidation of memory traces. These imply both thalamocortical and hippocampo-neocortical networks. Similarly, neuroimaging techniques demonstrated the experience-dependent changes in cerebral activity during sleep. Finally, recent works show the modulation during sleep of cerebral protein synthesis and expression of genes involved in neuronal plasticity.

Robust path integration in the entorhinal grid cell system with hippocampal feed-back

Animals are able to update their knowledge about their current position solely by integrating the speed and the direction of their movement, which is known as path integration. Recent discoveries suggest that grid cells in the medial entorhinal cortex might perform some of the essential underlying computations of path integration. However, a major concern over path integration is that as the measurement of speed and direction is inaccurate, the representation of the position will become increasingly unreliable. In this paper, we study how allothetic inputs can be used to continually correct the accumulating error in the path integrator system. We set up the model of a mobile agent equipped with the entorhinal representation of idiothetic (grid cell) and allothetic (visual cells) information and simulated its place learning in a virtual environment. Due to competitive learning, a robust hippocampal place code emerges rapidly in the model. At the same time, the hippocampo-entorhinal feed-back connections are modified via Hebbian learning in order to allow hippocampal place cells to influence the attractor dynamics in the entorhinal cortex. We show that the continuous feed-back from the integrated hippocampal place representation is able to stabilize the grid cell code.

Functional differentiation and cooperation among the hippocampal subregions in rats to effect spatial memory processes

We investigated the roles of the hippocampal subregions and intrahippocampal networks in effecting spatial reference and working processes. The results showed that the dentate gyrus plays a key role in encoding both types of spatial memory. Lesions in the dentate gyrus caused severe impairment in the acquisition of the Morris water maze and delayed matching-to-place tasks as compared to those in the other hippocampal subregions (Exp. 1). Further, there was functional cooperation between CA3 and CA1 via the Schaffer collaterals and the hippocampal commissure in the performance of both types of spatial memory tasks. Among the rats with intact hippocampal commissure, those with both contralateral and ipsilateral CA1/CA3 lesions showed a similar performance (Exp. 2A); however, among the rats with transected hippocampal commissure, those with the contralateral CA1/CA3 lesions showed a more disruptive performance than the rats with the ipsilateral CA1/CA3 lesions (Exp. 2B). This study suggests that the hippocampus is the functional unit for spatial reference and working memory processes, including differential functions and functional cooperation among the hippocampal subregions.

Distinct memory signatures in the hippocampus: intentional States distinguish match and mismatch enhancement signals

Incoming events that match or mismatch stored representations are thought to influence the ability of the hippocampus to switch between memory encoding and retrieval modes. Electrophysiological work has dissociated match and mismatch signals in the monkey perirhinal cortex, where match signals were selective for matches to goal states, whereas mismatch signals were not modulated by intention (Miller and Desimone, 1994). To investigate whether the theoretically important relational match and mismatch signals in the hippocampus are modulated by goal states, we fully crossed whether a probe stimulus relationally matched or mismatched a previously perceived image or goal state. Subjects performed two working memory tasks in which they either responded "yes" to probes that were identical to the previous sample scene or, after performing a relational manipulation of the scene, responded "yes" only to a probe that was identical to this perceptually novel image. Using functional magnetic resonance imaging, we found evidence for relational match enhancements bilaterally in the hippocampus that were selective for matches between the probe stimulus and goal state, but were not modulated by whether that goal was perceptually novel. Moreover, we found evidence for a complementary hippocampal mismatch enhancement that was triggered by stimuli containing salient perceptual manipulations. Our results provided evidence for parallel memory signatures in the hippocampus: a controlled match signal that can detect matches to internally generated goal states and an automatic mismatch signal that can identify unpredicted perceptual novelty.

A role for hilar cells in pattern separation in the dentate gyrus: a computational approach

We present a simple computational model of the dentate gyrus to evaluate the hypothesis that pattern separation, defined as the ability to transform a set of similar input patterns into a less-similar set of output patterns, is dynamically regulated by hilar neurons. Prior models of the dentate gyrus have generally fallen into two categories: simplified models that have focused on a single granule cell layer and its ability to perform pattern separation, and large-scale and biophysically realistic models of dentate gyrus, which include hilar cells, but which have not specifically addressed pattern separation. The present model begins to bridge this gap. The model includes two of the major subtypes of hilar cells: excitatory hilar mossy cells and inhibitory hilar interneurons that receive input from and project to the perforant path terminal zone (HIPP cells). In the model, mossy cells and HIPP cells provide a mechanism for dynamic regulation of pattern separation, allowing the system to upregulate and downregulate pattern separation in response to environmental and task demands. Specifically, pattern separation in the model can be strongly decreased by decreasing mossy cell function and/or by increasing HIPP cell function; pattern separation can be increased by the opposite manipulations. We propose that hilar cells may similarly mediate dynamic regulation of pattern separation in the dentate gyrus in vivo, not only because of their connectivity within the dentate gyrus, but also because of their modulation by brainstem inputs and by the axons that "backproject" from area CA3 pyramidal cells.

New experiences enhance coordinated neural activity in the hippocampus

The acquisition of new memories for places and events requires synaptic plasticity in the hippocampus, and plasticity depends on temporal coordination among neurons. Spatial activity in the hippocampus is relatively disorganized during the initial exploration of a novel environment, however, and it is unclear how neural activity during the initial stages of learning drives synaptic plasticity. Here we show that pairs of CA1 cells that represent overlapping novel locations are initially more coactive and more precisely coordinated than are cells representing overlapping familiar locations. This increased coordination occurs specifically during brief, high-frequency events (HFEs) in the local field potential that are similar to ripples and is not associated with better coordination of place-specific neural activity outside of HFEs. As novel locations become more familiar, correlations between cell pairs decrease. Thus, hippocampal neural activity during learning has a unique structure that is well suited to induce synaptic plasticity and to allow for rapid storage of new memories.

Qualitatively different hippocampal subfield engagement emerges with mastery of a spatial memory task by rats

The parallel, entorhinal cortex projections to different hippocampal regions potentially support separate mnemonic functions. To examine this possibility, rats were trained in a radial-arm maze task so that hippocampal activity could be compared after "early" (two sessions) or "late" (five sessions) learning. Induction of the immediate-early gene Zif268 was then measured, so revealing possible activity differences across hippocampal subfields and the parahippocampal cortices. Each rat in the two experimental groups (early, late) was also yoked to a control rat that obtained the same number of rewards, visited the same number of maze arms, and spent a comparable amount of time in the maze. Although overall Zif268 levels did not distinguish the four groups, significant correlations were found between spatial memory performance and levels of dentate gyrus Zif268 expression in the early but not the late training group. Conversely, hippocampal fields CA3 and CA1 Zif268 expression correlated with performance in the late but not the early training group. This reversal in the correlation pattern was echoed by structural equation modeling, which revealed dynamic changes in effective network connectivity. With early training, the dentate gyrus appeared to help determine CA1 activity, but by late training the dentate gyrus reduced its neural influence. Furthermore, CA1 was distinguished from CA3, each subfield developing opposite relations with task mastery. Thus, functional entorhinal cortex coupling with CA1 activity became more direct with additional training, so producing a trisynaptic circuit bypass. The present study reveals qualitatively different patterns of hippocampal subfield engagement dependent on task demands and mastery.

Context learning in the rodent hippocampus

We present a Bayesian statistical theory of context learning in the rodent hippocampus. While context is often defined in an experimental setting in relation to specific background cues or task demands, we advance a single, more general notion of context that suffices for a variety of learning phenomena. Specifically, a context is defined as a statistically stationary distribution of experiences, and context learning is defined as the problem of how to form contexts out of groups of experiences that cluster together in time. The challenge of context learning is solving the model selection problem: How many contexts make up the rodent's world? Solving this problem requires balancing two opposing goals: minimize the variability of the distribution of experiences within a context and minimize the likelihood of transitioning between contexts. The theory provides an understanding of why hippocampal place cell remapping sometimes develops gradually over many days of experience and why even consistent landmark differences may need to be relearned after other environmental changes. The theory provides an explanation for progressive performance improvements in serial reversal learning, based on a clear dissociation between the incremental process of context learning and the relatively abrupt context selection process. The impact of partial reinforcement on reversal learning is also addressed. Finally, the theory explains why alternating sequence learning does not consistently result in unique context-dependent sequence representations in hippocampus.

Hypobaric hypoxia damages the hippocampal pyramidal neurons in the rat brain

Hypobaric hypoxia (HH), a predisposing environmental condition at high altitude (HA), encountered by many mountaineers, jeopardizes their normal physiology like motor coordination and cognitive functions. A large body of evidence shows that HH has deleterious effect on cognitive functions. Among them the hippocampal dependent memory deficit is well known. However, our current understanding of the mechanistic details of cognitive deficits at HA remains largely unclear and hence limits a solution for this problem. Therefore, the present study was designed to investigate the temporal component of the hippocampal pyramidal neuron damage in the rat brain subjected to chronic HH exposure. Three groups (sham HH, 3 days HH and 7 days HH) of rats were exposed to simulated HH equivalent to 6100 m in an animal decompression chamber for 3 or 7 days. Later, the hippocampal (CA1 and CA3) neurons were analysed for the cell morphology, neurodegeneration and DNA fragmentation. The CA1 and CA3 neurons showed HH induced neuronal pyknosis, cell shrinkage, and consequent inter-cellular vacuolization in the CA1 and CA3 areas. In addition, the total neuron (intact) numbers and mean surface area were decreased. The number of dead neurons increased significantly following exposure to HH for 3 or 7 days. The neurodegenerative (Fluoro jade B) and apoptotic (TUNEL) markers were more positive in CA1 and CA3 neurons. The magnitude of morphological changes, neurodegeneration and apoptosis was enhanced in 7 days HH group than 3 days HH group. Our studies indicate that CA3 neurons are more vulnerable to HH than CA1 neurons, and that may destabilize the neural circuits in the hippocampus and thus cause memory dysfunction.

Slowness and sparseness lead to place, head-direction, and spatial-view cells

We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system []. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.

Prevalence of epileptiform activity in healthy children during sleep

BACKGROUND

The term epileptiform discharge typically refers to interictal paroxysmal activity that occurs more commonly during sleep. This type of paroxysmal activity does not include the electroencephalographic (EEG) activity observed during a seizure. The prevalence of epileptiform activity in the general pediatric population is unknown.

METHODS

Polysomnographic (PSG) studies were conducted in otherwise healthy children recruited from the general population and with no previous history of seizures or any other medical conditions. All sleep studies included an eight-lead EEG montage. Spike and sharp waves, either alone or accompanied by slow waves, occurring singly or in bursts lasting <5s were considered as representing epileptiform activity.

RESULTS

Nine hundred seventy children underwent overnight PSG. In 14 children, evidence of epileptiform activity, in the absence of any additional abnormality in the PSG, occurred. Thus, the prevalence of epileptiform activity was 1.45%. Epileptiform patterns found were either spike or spike and wave and were more prominent during non-rapid eye movement (NREM) sleep, with 11 patients presenting spike and spike and wave patterns in the centro-temporal regions. Four of the six children who underwent neurocognitive tests exhibited abnormal findings in areas of behavior, attention, hyperactivity, and learning.

CONCLUSION

Epileptiform activity in otherwise healthy children from the community is relatively frequent and, if confirmed by prospective studies, could be associated with suboptimal cognitive and behavioral functions. Increased awareness by sleep professionals and use of PSG montage that includes temporal leads and >2 standard EEG leads should facilitate the detection of epileptiform activity in children.

Three-dimensional reconstruction of the axon arbor of a CA3 pyramidal cell recorded and filled in vivo

The three-dimensional intrahippocampal distribution of axon collaterals of an in vivo filled CA3c pyramidal cell was investigated. The neuron was filled with biocytin in an anesthetized rat and the collaterals were reconstructed with the aid of a NeuroLucida program from 48 coronal sections. The total length of the axon collaterals exceeded 0.5 m, with almost 40,000 synaptic boutons. The majority of the collaterals were present in the CA1 region (70.0%), whereas 27.6% constituted CA3 recurrent collaterals with the remaining minority of axons returning to the dentate gyrus. The axon arbor covered more than two thirds of the longitudinal axis of the hippocampus, and the terminals were randomly distributed both locally and distally from the soma. We suggest that the CA3 system can be conceptualized as a single-module, in which nearby and distant targets are contacted by the same probability (similar to a mathematically defined random graph). This arrangement, in combination with the parallel input granule cells and parallel output CA1 pyramidal cells, appears ideal for segregation and integration of information and memories.

Entorhinal cortex of the monkey: VII. intrinsic connections

The organization of intrinsic connections within the entorhinal cortex was investigated in Macaca fascicularis monkeys. Anterograde tracers ((3)H-amino acids, Phaseolus vulgaris-leucoagglutinin, biotinylated dextran amine, or Fluoro-Ruby) were injected into the deep or superficial layers of the entorhinal cortex in 24 animals. These injections labeled extensive intrinsic projections that terminated throughout all layers of the entorhinal cortex. Labeling was typically continuous i.e., there was no evidence of a patchy or columnar organization. Each injection produced a rostrocaudally oriented band of labeled fibers and terminals that extended for one-third to one-half of the length of the entorhinal cortex. The more extensive distributions of labeled fibers were more typical of caudally placed injection sites. Taken together, the projections identified at least two mediolaterally differentiated bands: a lateral band that encompasses fields Elr, Elc, and the most lateral aspect of fields Ec and Ecl and a wider, medially situated band that encompasses much of fields Er, Ei, Ec, and Ecl. We obtained some evidence that field Eo constitutes a third, very medially placed band. The rostrocaudal organization of labeled fibers and the extent of labeling within the deep and superficial layers were unrelated to the laminar position of the injection. These data suggest that intrinsic associatonal connections in the monkey entorhinal cortex are organized into separate associational networks. Our findings are discussed with reference to the role of interlaminar connections in mediating physiological interactions between the neocortex and the hippocampus.

Reduced reactivity to novelty, impaired social behavior, and enhanced basal synaptic excitatory activity in perforant path projections to the dentate gyrus in young adult mice deficient in the neural cell adhesion molecule CHL1

The neural cell adhesion molecule CHL1 is implicated in neural development in the mouse and has been related to psychiatric disorders in humans. Here we report that mice constitutively deficient for CHL1 display reduced reactivity to environmental stimuli and reduced expression of social behaviors, whereas cognitive, motor and olfactory functions are normal. Basal synaptic transmission and plasticity in seven major excitatory connections in the hippocampus were analyzed to test whether dysfunctions in this brain region, which controls complex behaviors, correlate with the behavioral alterations of CHL1 deficient mice. We found that basal synaptic transmission in lateral and medial perforant path projections to the dentate gyrus is elevated in CHL1-deficient mice. Taking in consideration the function of these synapses in processing information from cortical areas, we hypothesize that constitutive ablation of CHL1 leads to reduced capability to react to external stimuli due to dysfunctions in the dentate gyrus.

Which computational mechanisms operate in the hippocampus during novelty detection?

A fundamental property of adaptive behavior is the ability to rapidly distinguish what is novel from what is familiar in our environment. Empirical evidence and computational work have provided biologically plausible models of the neural substrate and mechanisms underlying the coding of stimulus novelty in the perirhinal cortex. In this article, we highlight the importance of a different category of novelty, namely associative novelty, which has received relatively little attention, despite its clear ecological importance. While previous studies in both animals and humans have documented hippocampal responses in relation to associative novelty, a key issue concerning the computations underlying these novelty signals has not been previously addressed. We argue that this question has importance not only for our understanding of novelty processing, but also for advancing our knowledge of the fundamental computational operations performed by the hippocampus. We suggest a different approach to this problem, and discuss recent evidence supporting the hypothesis that the hippocampus operates as a comparator during the processing of associative novelty, generating mismatch/novelty signals when prior predictions are violated by sensory reality. We also draw on conceptual similarities between associative novelty and contextual novelty to suggest that empirical findings from these two seemingly distant research fields accord with the operation of a comparator mechanism during novelty detection more generally. We therefore conclude that a comparator mechanism may underlie the role of the hippocampus not only in detecting occurrences that are unexpected given specific associatively retrieved predictions, but also events that violate more abstract properties of the experimental context.

Electrical induction of spikes in the hippocampus impairs recognition capacity and spatial memory in rats

In clinical studies, interictal EEG spikes (IS) have been associated with numerous neuropsychological abnormalities, ranging from transitory cognitive impairment to epileptic encephalopathies. Understanding the pathophysiological mechanisms of IS has been hampered by the lack of validated animal models. To mimic IS, a stimulating microelectrode was implanted in the ventral hippocampal commissure and a recording microelectrode in the CA1 region of the hippocampus of normal male rats. Spike patterns were induced using a series of electrical pulses 10-30 ms in duration with a frequency of 0.5-2Hz and a current of 0.2mA. The commissural stimulation-evoked population discharges in the hippocampus resembled naturally occurring IS in epileptic rats and, in no cases, resulted in behavioral seizures. For behavioral testing, the Morris water maze, radial arm maze, and object recognition tasks were used. Spikes were induced during sleep between the two sets of water maze trials; during the trials in the radial arm maze task; and prior to the sample phase and during the delay periods in the object recognition task. We demonstrated that rats that received spikes took longer to reach the escape platform in the second set of water maze trials; had significantly more reference errors and required more trials to complete the radial arm maze task; and had lower investigation ratios in the object recognition task. The results indicate that induction of spikes in the hippocampus results in impairment of spatial reference and nonspatial object recognition memory.

Evolution of declarative memory

The present review considers research on the hippocampus and related areas from humans and experimental animals and makes three main points. First, many of the anatomical details of the hippocampus and adjacent cortical areas in the parahippocampal region are conserved across mammals. Second, the functional role of these areas in declarative memory is also conserved across species. Third, an evolutionary approach will be key to understanding exactly how the local circuitry of the hippocampus and parahippocampal region supports declarative memory. To highlight the utility of this approach, a schematic model is described in which separate streams of spatial and nonspatial information converge on the hippocampus. By this view, a fundamental function of the mammalian hippocampus is to combine incoming information about spatial context from the postrhinal (parahippocampal in primates) cortex and medial entorhinal area with incoming information about nonspatial items from the perirhinal cortex and lateral entorhinal area. The underlying neurobiological computations that arise from local circuitry enable item-in-context memory and are proposed to be fundamental to many examples of declarative memory, including episodic memory in humans and spatial memory in experimental animals.

Memory formation by neuronal synchronization

Cognitive functions not only depend on the localization of neural activity, but also on the precise temporal pattern of activity in neural assemblies. Synchronization of action potential discharges provides a link between large-scale EEG recordings and cellular plasticity mechanisms. Here, we focus on the role of neuronal synchronization in different frequency domains for the subsequent stages of memory formation. Recent EEG studies suggest that synchronized neural activity in the gamma frequency range (around 30-100 Hz) plays a functional role for the formation of declarative long-term memories in humans. On the cellular level, gamma synchronization between hippocampal and parahippocampal regions may induce LTP in the CA3 region of the hippocampus. In order to encode spatial locations or sequences of multiple items and to guarantee a defined temporal order of memory processing, synchronization in the gamma frequency range has to be accompanied by a stimulus-locked phase reset of ongoing theta oscillations. Simultaneous gamma- and theta-dependent plasticity leads to complex learning rules required for realistic declarative memory formation. Subsequently, consolidation of declarative memories may occur via replay of newly acquired patterns in so-called sharp wave-ripple complexes, predominantly during slow-wave sleep. These irregular bursts induce longer lasting forms of synaptic plasticity in output regions of the hippocampus and in the neocortex. In summary, synchronization of neural assemblies in different frequency ranges induces specific forms of cellular plasticity during subsequent stages of memory formation.

Hippocampal CA1 spiking during encoding and retrieval: relation to theta phase

The hippocampal theta rhythm is a prominent oscillation in the field potential observed throughout the hippocampus as a rat investigates stimuli in the environment. A recent computational model [Hasselmo, M. E., Bodelon, C., & Wyble, B. P. (2002a). A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Computation, 14, 793-817. Neuromodulation, theta rhythm and rat spatial navigation. Neural Networks, 15, 689-707] suggested that the theta rhythm allows the hippocampal formation to alternate rapidly between conditions that promote memory encoding (strong synaptic input from entorhinal cortex to areas CA3 and CA1) and conditions that promote memory retrieval (strong synaptic input from CA3 to CA1). That model predicted that the preferred theta phase of CA1 spiking should differ for information being encoded versus information being retrieved. In the present study, the spiking activity of CA1 pyramidal cells was recorded while rats performed either an odor-cued delayed nonmatch-to-sample recognition memory test or an object recognition memory task based on the animal's spontaneous preference for novelty. In the test period of both tasks, the preferred theta phase exhibited by CA1 pyramidal cells differed between moments when the rat inspected repeated (match) and non-repeated (nonmatch) items. Also in the present study, additional modeling work extended the previous model to address the mean phase of CA1 spiking associated with stimuli inducing varying levels of retrieval relative to encoding, ranging from novel nonmatch stimuli with no retrieval to highly familiar repeated stimuli with extensive retrieval. The modeling results obtained here demonstrated that the experimentally observed phase differences are consistent with different levels of CA3 synaptic input to CA1 during recognition of repeated items.

Memory Capacity for Sequences in a Recurrent Network with Biological Constraints

The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage and replay of sequences of patterns that represent behavioral events. Here we present a theoretical framework to calculate a sparsely connected network's capacity to store such sequences. As in CA3, only a limited subset of neurons in the network is active at any one time, pattern retrieval is subject to error, and the resources for plasticity are limited. Our analysis combines an analytical mean field approach, stochastic dynamics, and cellular simulations of a time-discrete McCulloch-Pitts network with binary synapses. To maximize the number of sequences that can be stored in the network, we concurrently optimize the number of active neurons, that is, pattern size, and the firing threshold. We find that for one-step associations (i.e., minimal sequences), the optimal pattern size is inversely proportional to the mean connectivity c, whereas the optimal firing threshold is independent of the connectivity. If the number of synapses per neuron is fixed, the maximum number P of stored sequences in a sufficiently large, nonmodular network is independent of its number N of cells. On the other hand, if the number of synapses scales as the network size to the power of 3/2, the number of sequences P is proportional to N. In other words, sequential memory is scalable. Further-more, we find that there is an optimal ratio r between silent and nonsilent synapses at which the storage capacity α = P/[c (1 +r)N] assumes a maximum. For long sequences, the capacity of sequential memory is about one order of magnitude below the capacity for minimal sequences, but otherwise behaves similar to the case of minimal sequences. In a biologically inspired scenario, the information content per synapse is far below theoretical optimality, suggesting that the brain trades off error tolerance against information content in encoding sequential memories.