Goal-oriented inference of environment from redundant observations.

The agent learns to organize decision behavior to achieve a behavioral goal, such as reward maximization, and reinforcement learning is often used for this optimization. Learning an optimal behavioral strategy is difficult under the uncertainty that events necessary for learning are only partially observable, called as Partially Observable Markov Decision Process (POMDP). However, the real-world environment also gives many events irrelevant to reward delivery and an optimal behavioral strategy. The conventional methods in POMDP, which attempt to infer transition rules among the entire observations, including irrelevant states, are ineffective in such an environment. Supposing Redundantly Observable Markov Decision Process (ROMDP), here we propose a method for goal-oriented reinforcement learning to efficiently learn state transition rules among reward-related "core states" from redundant observations. Starting with a small number of initial core states, our model gradually adds new core states to the transition diagram until it achieves an optimal behavioral strategy consistent with the Bellman equation. We demonstrate that the resultant inference model outperforms the conventional method for POMDP. We emphasize that our model only containing the core states has high explainability. Furthermore, the proposed method suits online learning as it suppresses memory consumption and improves learning speed.

Reward expectation enhances action-related activity of nigral dopaminergic and two striatal output pathways.

Neurons comprising nigrostriatal system play important roles in action selection. However, it remains unclear how this system integrates recent outcome information with current action (movement) and outcome (reward or no reward) information to achieve appropriate subsequent action. We examined how neuronal activity of substantia nigra pars compacta (SNc) and dorsal striatum reflects the level of reward expectation from recent outcomes in rats performing a reward-based choice task. Movement-related activity of direct and indirect pathway striatal projection neurons (dSPNs and iSPNs, respectively) were enhanced by reward expectation, similarly to the SNc dopaminergic neurons, in both medial and lateral nigrostriatal projections. Given the classical basal ganglia model wherein dopamine stimulates dSPNs and suppresses iSPNs through distinct dopamine receptors, dopamine might not be the primary driver of iSPN activity increasing following higher reward expectation. In contrast, outcome-related activity was affected by reward expectation in line with the classical model and reinforcement learning theory, suggesting purposive effects of reward expectation.

State-transition-free reinforcement learning in chimpanzees (Pan troglodytes).

The outcome of an action often occurs after a delay. One solution for learning appropriate actions from delayed outcomes is to rely on a chain of state transitions. Another solution, which does not rest on state transitions, is to use an eligibility trace (ET) that directly bridges a current outcome and multiple past actions via transient memories. Previous studies revealed that humans (Homo sapiens) learned appropriate actions in a behavioral task in which solutions based on the ET were effective but transition-based solutions were ineffective. This suggests that ET may be used in human learning systems. However, no studies have examined nonhuman animals with an equivalent behavioral task. We designed a task for nonhuman animals following a previous human study. In each trial, participants chose one of two stimuli that were randomly selected from three stimulus types: a stimulus associated with a food reward delivered immediately, a stimulus associated with a reward delivered after a few trials, and a stimulus associated with no reward. The presented stimuli did not vary according to the participants' choices. To maximize the total reward, participants had to learn the value of the stimulus associated with a delayed reward. Five chimpanzees (Pan troglodytes) performed the task using a touchscreen. Two chimpanzees were able to learn successfully, indicating that learning mechanisms that do not depend on state transitions were involved in the learning processes. The current study extends previous ET research by proposing a behavioral task and providing empirical data from chimpanzees.

Rat hippocampal CA1 region represents learning-related action and reward events with shorter latency than the lateral entorhinal cortex.

The hippocampus and entorhinal cortex are deeply involved in learning and memory. However, little is known how ongoing events are processed in the hippocampal-entorhinal circuit. By recording from head-fixed rats during action-reward learning, here we show that the action and reward events are represented differently in the hippocampal CA1 region and lateral entorhinal cortex (LEC). Although diverse task-related activities developed after learning in both CA1 and LEC, phasic activities related to action and reward events differed in the timing of behavioral event representation. CA1 represented action and reward events almost instantaneously, whereas the superficial and deep layers of the LEC showed a delayed representation of the same events. Interestingly, we also found that ramping activity towards spontaneous action was correlated with waiting time in both regions and exceeded that in the motor cortex. Such functional activities observed in the entorhinal-hippocampal circuits may play a crucial role for animals in utilizing ongoing information to dynamically optimize their behaviors.

Automated and parallelized spike collision tests to identify spike signal projections.

The spike collision test is a highly reliable technique to identify the axonal projection of a neuron recorded electrophysiologically for investigating functional spike information among brain areas. It is potentially applicable to more neuronal projections by combining multi-channel recording with optogenetic stimulation. Yet, it remains inefficient and laborious because an experimenter must visually select spikes in every channel and manually repeat spike collision tests for each neuron serially. Here, we automated spike collision tests for all channels in parallel (Multi-Linc analysis) in a multi-channel real-time processing system. The rat cortical neurons identified with this technique displayed physiological spike features consistent with excitatory projection neurons. Their antidromic spikes were similar in shape but slightly larger in amplitude compared with spontaneous spikes. In addition, we demonstrated simultaneous identification of reciprocal or bifurcating projections among cortical areas. Thus, our Multi-Linc analysis will be a powerful approach to elucidate interareal spike communication.

Memory trace imbalance in reinforcement and punishment systems can reinforce implicit choices leading to obsessive-compulsive behavior.

We may view most of our daily activities as rational action selections; however, we sometimes reinforce maladaptive behaviors despite having explicit environmental knowledge. In this study, we model obsessive-compulsive disorder (OCD) symptoms as implicitly learned maladaptive behaviors. Simulations in the reinforcement learning framework show that agents implicitly learn to respond to intrusive thoughts when the memory trace signal for past actions decays differently for positive and negative prediction errors. Moreover, this model extends our understanding of therapeutic effects of behavioral therapy in OCD. Using empirical data, we confirm that patients with OCD show extremely imbalanced traces, which are normalized by serotonin enhancers. We find that healthy participants also vary in their obsessive-compulsive tendencies, consistent with the degree of imbalanced traces. These behavioral characteristics can be generalized to variations in the healthy population beyond the spectrum of clinical phenotypes.

Computerized intertemporal choice task in chimpanzees (Pan troglodytes) with/without postreward delay.

In intertemporal choice (ITC) tasks, animals are presented with alternative choices between a smaller reward that becomes available sooner and a larger reward that becomes available later. To equate the duration of a trial across the 2 options, postreward delays (PRDs) are inserted after the delivery of the reward. Animals need to incorporate this to increase the long-term reward rate. However, recent studies suggest that they have difficulty understanding the contingency associated with PRDs. Previous research indicates that chimpanzees exhibit particularly great self-control in ITC tasks, but it remains unclear whether chimpanzees do so when considering PRDs. Therefore, we used touchscreen experiments to explore chimpanzee intertemporal preferences when trial duration was equated by a PRD as well as when the PRD was eliminated. The computerized setting was used to try to control delay length flexibly and precisely while reducing the impact of the interaction with human experimenters. Moreover, choice options were presented on touchscreens using symbolic cues. This may reduce the impact of seeing food rewards on making a choice (i.e., the animals' robust tendency to reach for the larger amount of food). In an ITC task in which the trial duration was equated, 4 chimpanzees preferred larger rewards but chose smaller rewards more often when the ratio of the reward amount was smaller. In an ITC task with no PRDs, 2 of 4 chimpanzees did switch their preference to smaller rewards and enhanced the reward rate although this result should be interpreted in light of some methodological limitations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A spike analysis method for characterizing neurons based on phase locking and scaling to the interval between two behavioral events.

Standard analysis of neuronal functions assesses the temporal correlation between animal behaviors and neuronal activity by aligning spike trains with the timing of a specific behavioral event, e.g., visual cue. However, spike activity is often involved in information processing dependent on a relative phase between two consecutive events rather than a single event. Nevertheless, less attention has so far been paid to such temporal features of spike activity in relation to two behavioral events. Here, we propose "Phase-Scaling analysis" to simultaneously evaluate the phase locking and scaling to the interval between two events in task-related spike activity of individual neurons. This analysis method can discriminate conceptual "scaled"-type neurons from "nonscaled"-type neurons using an activity variation map that combines phase locking with scaling to the interval. Its robustness was validated by spike simulation using different spike properties. Furthermore, we applied it to analyzing actual spike data from task-related neurons in the primary visual cortex (V1), posterior parietal cortex (PPC), primary motor cortex (M1), and secondary motor cortex (M2) of behaving rats. After hierarchical clustering of all neurons using their activity variation maps, we divided them objectively into four clusters corresponding to nonscaled-type sensory and motor neurons and scaled-type neurons including sustained and ramping activities, etc. Cluster/subcluster compositions for V1 differed from those of PPC, M1, and M2. The V1 neurons showed the fastest functional activities among those areas. Our method was also applicable to determine temporal "forms" and the latency of spike activity changes. These findings demonstrate its utility for characterizing neurons.NEW & NOTEWORTHY Phase-Scaling analysis is a novel technique to unbiasedly characterize the temporal dependency of functional neuron activity on two behavioral events and objectively determine the latency and form of the activity change. This powerful analysis can uncover several classes of latently functioning neurons that have thus far been overlooked, which may participate differently in intermediate processes of a brain function. The Phase-Scaling analysis will yield profound insights into neural mechanisms for processing internal information.

Differential Changes in the Lateralized Activity of Identified Projection Neurons of Motor Cortex in Hemiparkinsonian Rats.

In the parkinsonian state, the motor cortex and basal ganglia (BG) undergo dynamic remodeling of movement representation. One such change is the loss of the normal contralateral lateralized activity pattern. The increase in the number of movement-related neurons responding to ipsilateral or bilateral limb movements may cause motor problems, including impaired balance, reduced bimanual coordination, and abnormal mirror movements. However, it remains unknown how individual types of motor cortical neurons organize this reconstruction. To explore the effect of dopamine depletion on lateralized activity in the parkinsonian state, we used a partial hemiparkinsonian model [6-hydroxydopamine (6-OHDA) lesion] in Long-Evans rats performing unilateral movements in a right-left pedal task, while recording from primary (M1) and secondary motor cortex (M2). The lesion decreased contralateral preferred activity in both M1 and M2. In addition, this change differed among identified intratelencephalic (IT) and pyramidal tract (PT) cortical projection neurons, depending on the cortical area. We detected a decrease in lateralized activity only in PT neurons in M1, whereas in M2, this change was observed in IT neurons, with no change in the PT population. Our results suggest a differential effect of dopamine depletion in the lateralized activity of the motor cortex, and suggest possible compensatory changes in the contralateral hemisphere.

Ipsilateral-Dominant Control of Limb Movements in Rodent Posterior Parietal Cortex.

It is well known that the posterior parietal cortex (PPC) and frontal motor cortices in primates preferentially control voluntary movements of contralateral limbs. The PPC of rats has been defined based on patterns of thalamic and cortical connectivity. The anatomical characteristics of this area suggest that it may be homologous to the PPC of primates. However, its functional roles in voluntary forelimb movements have not been well understood, particularly in the lateralization of motor limb representation; that is, the limb-specific activity representations for right and left forelimb movements. We examined functional spike activity of the PPC and two motor cortices, the primary motor cortex (M1) and the secondary motor cortex (M2), when head-fixed male rats performed right or left unilateral movements. Unlike primates, PPC neurons in rodents were found to preferentially represent ipsilateral forelimb movements, in contrast to the contralateral preference of M1 and M2 neurons. Consistent with these observations, optogenetic activation of PPC and motor cortices, respectively, evoked ipsilaterally and contralaterally biased forelimb movements. Finally, we examined the effects of optogenetic manipulation on task performance. PPC or M1 inhibition by optogenetic GABA release shifted the behavioral limb preference contralaterally or ipsilaterally, respectively. In addition, weak optogenetic PPC activation, which was insufficient to evoke motor responses by itself, shifted the preference ipsilaterally; although similar M1 activation showed no effects on task performance. These paradoxical observations suggest that the PPC plays evolutionarily different roles in forelimb control between primates and rodents.SIGNIFICANCE STATEMENT In rodents, the primary and secondary motor cortices (M1 and M2, respectively) are involved in voluntary movements with contralateral preference. However, it remains unclear whether and how the posterior parietal cortex (PPC) participates in controlling multiple limb movements. We recorded functional activity from these areas using a behavioral task to monitor movements of the right and left forelimbs separately. PPC neurons preferentially represented ipsilateral forelimb movements and optogenetic PPC activation evoked ipsilaterally biased forelimb movements. Optogenetic PPC inhibition via GABA release shifted the behavioral limb preference contralaterally during task performance, whereas weak optogenetic PPC activation, which was insufficient to evoke motor responses by itself, shifted the preference ipsilaterally. Our findings suggest rodent PPC contributes to ipsilaterally biased motor response and/or planning.

Area-specific Modulation of Functional Cortical Activity During Block-based and Trial-based Proactive Inhibition.

Animals can suppress their behavioral response in advance according to changes in environmental context (proactive inhibition: delaying the start of response), a process in which several cortical areas may participate. However, it remains unclear how this process is adaptively regulated according to contextual changes on different timescales. To address the issue, we used an improved stop-signal task paradigm to behaviorally and electrophysiologically characterize the temporal aspect of proactive inhibition in head-fixed rats. In the task, they must respond to a go cue as quickly as possible (go trial), but did not have to respond if a stop cue followed the go cue (stop trial). The task alternated between a block of only go trials (G-block) and a block of go-and-stop trials (GS-block). We observed block-based and trial-based proactive inhibition (emerging in GS-block and after stop trial, respectively) by behaviorally evaluating the delay in reaction time in correct go trials depending on contextual changes on different timescales. We electrophysiologically analyzed task-related neuronal activity in the primary and secondary motor, posterior parietal, and orbitofrontal cortices (M1, M2, PPC, and OFC, respectively). Under block-based proactive inhibition, spike activity of cue-preferring OFC neurons was attenuated continuously, while M1 and M2 activity was enhanced during motor preparation. Subsequently, M1 activity was attenuated during motor decision/execution. Under trial-based proactive inhibition, the OFC activity was continuously enhanced, and PPC and M1 activity was also enhanced shortly during motor decision/execution. These results suggest that different cortical mechanisms underlie the two types of proactive inhibition in rodents.

Monitoring and Updating of Action Selection for Goal-Directed Behavior through the Striatal Direct and Indirect Pathways.

The basal ganglia play key roles in adaptive behaviors guided by reward and punishment. However, despite accumulating knowledge, few studies have tested how heterogeneous signals in the basal ganglia are organized and coordinated for goal-directed behavior. In this study, we investigated neuronal signals of the direct and indirect pathways of the basal ganglia as rats performed a lever push/pull task for a probabilistic reward. In the dorsomedial striatum, we found that optogenetically and electrophysiologically identified direct pathway neurons encoded reward outcomes, whereas indirect pathway neurons encoded no-reward outcome and next-action selection. Outcome coding occurred in association with the chosen action. In support of pathway-specific neuronal coding, light activation induced a bias on repeat selection of the same action in the direct pathway, but on switch selection in the indirect pathway. Our data reveal the mechanisms underlying monitoring and updating of action selection for goal-directed behavior through basal ganglia circuits.

In Vivo Spiking Dynamics of Intra- and Extratelencephalic Projection Neurons in Rat Motor Cortex.

In motor cortex, 2 types of deep layer pyramidal cells send their axons to other areas: intratelencephalic (IT)-type neurons specifically project bilaterally to the cerebral cortex and striatum, whereas neurons of the extratelencephalic (ET)-type, termed conventionally pyramidal tract-type, project ipsilaterally to the thalamus and other areas. Although they have totally different synaptic and membrane potential properties in vitro, little is known about the differences between them in ongoing spiking dynamics in vivo. We identified IT-type and ET-type neurons, as well as fast-spiking-type interneurons, using novel multineuronal analysis based on optogenetically evoked spike collision along their axons in behaving/resting rats expressing channelrhodopsin-2 (Multi-Linc method). We found "postspike suppression" (~100 ms) as a characteristic of ET-type neurons in spike auto-correlograms, and it remained constant independent of behavioral conditions in functionally different ET-type neurons. Postspike suppression followed even solitary spikes, and spike bursts significantly extended its duration. We also observed relatively strong spike synchrony in pairs containing IT-type neurons. Thus, spiking dynamics in IT-type and ET-type neurons may be optimized differently for precise and coordinated motor control.

Distinct Laterality in Forelimb-Movement Representations of Rat Primary and Secondary Motor Cortical Neurons with Intratelencephalic and Pyramidal Tract Projections.

Two distinct motor areas, the primary and secondary motor cortices (M1 and M2), play crucial roles in voluntary movement in rodents. The aim of this study was to characterize the laterality in motor cortical representations of right and left forelimb movements. To achieve this goal, we developed a novel behavioral task, the Right-Left Pedal task, in which a head-restrained male rat manipulates a right or left pedal with the corresponding forelimb. This task enabled us to monitor independent movements of both forelimbs with high spatiotemporal resolution. We observed phasic movement-related neuronal activity (Go-type) and tonic hold-related activity (Hold-type) in isolated unilateral movements. In both M1 and M2, Go-type neurons exhibited bias toward contralateral preference, whereas Hold-type neurons exhibited no bias. The contralateral bias was weaker in M2 than M1. Moreover, we differentiated between intratelencephalic (IT) and pyramidal tract (PT) neurons using optogenetically evoked spike collision in rats expressing channelrhodopsin-2. Even in identified PT and IT neurons, Hold-type neurons exhibited no lateral bias. Go-type PT neurons exhibited bias toward contralateral preference, whereas IT neurons exhibited no bias. Our findings suggest a different laterality of movement representations of M1 and M2, in each of which IT neurons are involved in cooperation of bilateral movements, whereas PT neurons control contralateral movements.SIGNIFICANCE STATEMENT In rodents, the primary and secondary motor cortices (M1 and M2) are involved in voluntary movements via distinct projection neurons: intratelencephalic (IT) neurons and pyramidal tract (PT) neurons. However, it remains unclear whether the two motor cortices (M1 vs M2) and the two classes of projection neurons (IT vs PT) have different laterality of movement representations. We optogenetically identified these neurons and analyzed their functional activity using a novel behavioral task to monitor movements of the right and left forelimbs separately. We found that contralateral bias was reduced in M2 relative to M1, and in IT relative to PT neurons. Our findings suggest that the motor information processing that controls forelimb movement is coordinated by a distinct cell population.

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions.

KEY POINTS: There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions. ABSTRACT: Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement.

A balanced motor primitive framework can simultaneously explain motor learning in unimanual and bimanual movements.

Certain theoretical frameworks have successfully explained motor learning in either unimanual or bimanual movements. However, no single theoretical framework can comprehensively explain motor learning in both types of movement because the relationship between these two types of movement remains unclear. Although our recent model of a balanced motor primitive framework attempted to simultaneously explain motor learning in unimanual and bimanual movements, this model focused only on a limited subset of bimanual movements and therefore did not elucidate the relationships between unimanual movements and various bimanual movements. Here, we extend the balanced motor primitive framework to simultaneously explain motor learning in unimanual and various bimanual movements as well as the transfer of learning effects between unimanual and various bimanual movements; these phenomena can be simultaneously explained if the mean activity of each primitive for various unimanual movements is balanced with the corresponding mean activity for various bimanual movements. Using this balanced condition, we can reproduce the results of prior behavioral and neurophysiological experiments. Furthermore, we demonstrate that the balanced condition can be implemented in a simple neural network model.

Similarity in Neuronal Firing Regimes across Mammalian Species.

UNLABELLED: The architectonic subdivisions of the brain are believed to be functional modules, each processing parts of global functions. Previously, we showed that neurons in different regions operate in different firing regimes in monkeys. It is possible that firing regimes reflect differences in underlying information processing, and consequently the firing regimes in homologous regions across animal species might be similar. We analyzed neuronal spike trains recorded from behaving mice, rats, cats, and monkeys. The firing regularity differed systematically, with differences across regions in one species being greater than the differences in similar areas across species. Neuronal firing was consistently most regular in motor areas, nearly random in visual and prefrontal/medial prefrontal cortical areas, and bursting in the hippocampus in all animals examined. This suggests that firing regularity (or irregularity) plays a key role in neural computation in each functional subdivision, depending on the types of information being carried. SIGNIFICANCE STATEMENT: By analyzing neuronal spike trains recorded from mice, rats, cats, and monkeys, we found that different brain regions have intrinsically different firing regimes that are more similar in homologous areas across species than across areas in one species. Because different regions in the brain are specialized for different functions, the present finding suggests that the different activity regimes of neurons are important for supporting different functions, so that appropriate neuronal codes can be used for different modalities.

Balanced motor primitive can explain generalization of motor learning effects between unimanual and bimanual movements.

Motor learning in unimanual and bimanual planar reaching movements has been intensively investigated. Although distinct theoretical frameworks have been proposed for each of these reaching movements, the relationship between these movements remains unclear. In particular, the generalization of motor learning effects (transfer of learning effects) between unimanual and bimanual movements has yet to be successfully explained. Here, by extending a motor primitive framework, we analytically proved that the motor primitive framework can reproduce the generalization of learning effects between unimanual and bimanual movements if the mean activity of each primitive for unimanual movements is balanced to the mean for bimanual movements. In this balanced condition, the activity of each primitive is consistent with previously reported neuronal activity. The unimanual-bimanual balance leads to the testable prediction that generalization between unimanual and bimanual movements is more widespread to different reaching directions than generalization within respective movements. Furthermore, the balanced motor primitive can reproduce another previously reported phenomenon: the learning of different force fields for unimanual and bimanual movements.

Anomalous neuronal responses to fluctuated inputs.

The irregular firing of a cortical neuron is thought to result from a highly fluctuating drive that is generated by the balance of excitatory and inhibitory synaptic inputs. A previous study reported anomalous responses of the Hodgkin-Huxley neuron to the fluctuated inputs where an irregularity of spike trains is inversely proportional to an input irregularity. In the current study, we investigated the origin of these anomalous responses with the Hindmarsh-Rose neuron model, map-based models, and a simple mixture of interspike interval distributions. First, we specified the parameter regions for the bifurcations in the Hindmarsh-Rose model, and we confirmed that the model reproduced the anomalous responses in the dynamics of the saddle-node and subcritical Hopf bifurcations. For both bifurcations, the Hindmarsh-Rose model shows bistability in the resting state and the repetitive firing state, which indicated that the bistability was the origin of the anomalous input-output relationship. Similarly, the map-based model that contained bistability reproduced the anomalous responses, while the model without bistability did not. These results were supported by additional findings that the anomalous responses were reproduced by mimicking the bistable firing with a mixture of two different interspike interval distributions. Decorrelation of spike trains is important for neural information processing. For such spike train decorrelation, irregular firing is key. Our results indicated that irregular firing can emerge from fluctuating drives, even weak ones, under conditions involving bistability. The anomalous responses, therefore, contribute to efficient processing in the brain.

Spatial information enhanced by non-spatial information in hippocampal granule cells.

The hippocampus organizes sequential memory composed of non-spatial information (such as objects and odors) and spatial information (places). The dentate gyrus (DG) in the hippocampus receives two types of information from the lateral and medial entorhinal cortices. Non-spatial and spatial information is delivered respectively to distal and medial dendrites (MDs) of granule cells (GCs) within the molecular layer in the DG. To investigate the role of the association of those two inputs, we measured the response characteristics of distal and MDs of a GC in a rat hippocampal slice and developed a multi-compartment GC model with dynamic synapses; this model reproduces the response characteristics of the dendrites. Upon applying random inputs or input sequences generated by a Markov process to the computational model, it was found that a high-frequency random pulse input to distal dendrites (DDs) and, separately, regular burst inputs to MDs were effective for inducing GC activation. Furthermore, when the random and theta burst inputs were simultaneously applied to the respective dendrites, the pattern discrimination for theta burst input to MDs that caused slight GC activation was enhanced in the presence of random input to DDs. These results suggest that the temporal pattern discrimination of spatial information is originally involved in a synaptic characteristic in GCs and is enhanced by non-spatial information input to DDs. Consequently, the co-activation of two separate inputs may play a crucial role in the information processing on dendrites of GCs by usefully combing each temporal sequence.