BACKGROUND
hippocampal formation has been identified as an important substrate for declarative memory for a broad range of materials in humans  <cit> .
in contrast, in rodent studies, two views respectively hold that the hippocampus is dedicated to spatial memory processing  <cit>  and that it associates general memory items  <cit> .
regarding the spatial view, results of several analyses of the stability of place cells have shown that pattern separation and pattern completion are apparent in neuronal ensembles of the hippocampus  <cit> .
in support of the general view, several experiments directly showed activity related to match/non-match conditions using recognition memory tasks, such as a delayed non-matching-to-sample  task  <cit> .
spatial information can be regarded as multiple items that are mutually associated according to temporal relations  <cit> .
therefore, place cells might code multiple events constructing a place experienced in the past  <cit> .
from this viewpoint, the lines of evidence for the general and spatial views are not contradictory and are consistent with the view of the hippocampus as being capable of auto-associative functions to retrieve entire episodes  <cit> .
on the other hand, the matrix-like organization of the hippocampus with several inputs and outputs has inspired some researchers to propose the hippocampal comparator theory  <cit> , which suggests that the hippocampus supports comparison, which might be one element in the match/non-match judgements.
in this context, several lines of evidence obtained from analyses of single neurons in spatial and non-spatial behavioral tasks suggest that the hippocampus is critical for episodic-like representations.
nevertheless, our knowledge related to neuronal computations in the working brain of behaving animals is limited; most of it has been inferred exclusively from changes in the firing rates of individual cells accumulated through many trials  <cit> .
therefore, to understand the hippocampal function completely, the actual encoding of information by the hippocampal neuronal networks of multiple neurons in a single trial during memory tasks must be elucidated.
recently, some researchers have attempted to elucidate the functioning of neuronal networks of the cerebral cortex using an artificial neuronal network classifier as a decoder that enables us to analyze spatiotemporal firing patterns among all observed cells in a single trial  <cit> .
consequently, using multi-neuronal recording and an artificial neural network classifier as a decoder, we analyzed spatiotemporal firing patterns among cells in the hippocampal ca <dig> of rats.
we report its neuronal ensemble code in a single trial of a dnms task.
RESULTS
we specifically examined the activities of the neuronal ensembles to provide quantitative constraints for hippocampal function.
we used a decoding technique based on a linear classifier for neuronal ensembles .
the decoding approach consists of training and regularizing a classifier to learn the map from neuronal ensemble activity to each behavioral label  , as has been done similarly in recent studies of the inferior temporal and motor cortices  <cit> .
the classifier learns the map directly from the training sets and generalizes it to a novel ensemble activity instead of using prior knowledge of the probability distribution of the training sets.
the input comprises neuronal ensemble activities from simultaneously monitored cells such as those shown in figures  <dig> and  <dig>  after training a binary classifier using a leave-one-out cross-validation method, the classifier is useful to decode the ensemble activity in a novel trial of tasks.
using such classifiers that can be implemented easily in neuronal networks of the hippocampal ca <dig>  we can assess the lower bound on the information available in the ensemble activity in a single trial  <cit> .
classification performance in neuronal ensembles and combination
we used the classifier approach to determine the functional roles of the ensembles of hippocampal ca <dig> during the dnms task.
figure  <dig> presents the cross-validated performance of the classifier for each neuronal ensemble.
the spiking activity of the ensembles was sufficient to classify a match tone and non-match tone  with maximum accuracy of 96% over a  <dig> ms time interval .
similarly, we determined the functional roles of the hippocampal ensembles in classifying go and non-go responses  and high and low tones during sample and delay periods .
the hippocampal ensembles were not capable of classifying these roles with sufficient accuracy .
moreover, we compared correct and erroneous responses during the test periods , and low-test tone periods preceded by high sample tones  and high test tone periods preceded by low sample tones  .
the results show that the hippocampal ensembles were also not capable of classifying these with significant accuracy .
the performance values depicted in figure  <dig> portray how accurately downstream neurons were able to classify the functional roles in a single trial, as determined using the computation of a weighted sum of spikes over a  <dig> ms time interval.
on the other hand, the classifier performance of the neuronal ensembles, as well as that of the combination , was enhanced approximately linearly with the logarithm of the number of participating cells , indicating that the codes for the stimulus comparison are distributed across cells, unlike that described by the grandmother cell doctrine.
moreover, irrespective of the large number of cells in the combination, the accuracy of the combination was markedly lower than those of the ensembles over all the other examined time intervals .
time resolution of code for stimulus comparison
by investigating the degree to which classification performance depended on the bin size of the spike count, we examined the temporal resolution of the ensemble code.
bin sizes of 2- <dig> ms yielded better performance than larger bin sizes .
a 2-ms bin typically contained zero or one spike.
consequently a few spikes from a small number of neurons are sufficient to encode the stimulus comparison in the hippocampal ensembles.
discussion
in this study, the activity of small neuronal ensembles  in the hippocampal ca <dig> was used to classify the stimulus comparison with good accuracy over brief time intervals .
they were not useful to classify the stimulus perception, stimulus retention, or motor selection.
the accuracy of the ensembles for the stimulus comparison was markedly higher than that of the combination .
small neuronal ensembles in the hippocampal ca <dig> specifically code stimulus comparison
during test periods in which the rats prepare for go/no-go responses, we examined the stimulus comparison as well as the motor selection.
the motor selection of go/no-go responses contains the stimulus comparison of match/non-match tones because, in correct trials, go and no-go responses respectively correspond to non-match and match tones.
it is possible that the low accuracy of the ensembles for the motor selection suggest that the activities of the neuronal ensembles are not useful to classify the stimulus comparison.
to verify the stimulus comparison without the influence of the motor functions, we examined ensemble activities during match and non-match tones to which identical behavioral responses  were conducted.
moreover, to exclude the influences of correct and erroneous responses and the particular stimuli being presented, we examined the classification performance of the ensemble activity in relation to the correct-error difference and the particular-stimulus presentation.
the results show that, using a linear classifier that can be realized easily in downstream neurons by summating appropriately weighted inputs, we can clearly characterize that at the ensemble level, the most available information in the hippocampal ca <dig> in each single trial is specifically the stimulus comparison: it is neither the correct-error difference nor the particular-stimulus presentation.
based on the results of ensemble analyses on a trial-to-trial basis, deadwyler and colleagues inferred multiple representation and conjunctive encoding in activities of small hippocampal ensembles consisting of  <dig> neurons  <cit> .
in contrast with the present results, they showed that the stimulus comparison in the hippocampal ensembles was highly correlated with correct and erroneous responses.
the reason for the inconsistent results might be differences in the tasks  and differences in the ensemble analysis tools .
furthermore, because we examined neuronal ensemble activities only in the hippocampal ca <dig>  the activity of the hippocampal ca <dig> analyzed in the deadwyler's study might explain the inconsistency of the results.
the results of the present study illustrate that small neuronal ensembles in the hippocampal ca <dig> are specifically dedicated to stimulus comparison.
the results support the notion that the hippocampus contributes to memory by identifying consistencies across experiences that constitute new associations, as reported from some previous studies  <cit> .
the classification performance for the stimulus comparison of neuronal ensembles is better than that of their combination
several lines of evidence  <cit>  suggested that firing rate modulations of individual neurons and spike timing among neurons contain information in the neuronal ensembles.
given that the small neuronal ensembles in the hippocampal ca <dig> contains information related only to the firing rate modulations of individual neurons, the classification performance of the combination of all neurons in all the ensembles recorded from different sessions is expected to be the sum of the performance of the ensembles.
however, in the present study, almost all classification performances of small neuronal ensembles in the hippocampal ca <dig> for the stimulus comparison were higher than that of the combination.
moreover, the ensembles yielded better performance in a 2- <dig> ms window.
from this perspective, we presume that the timing of spikes of 2- <dig> ms resolution in the ensembles recorded in the identical session, such as second or higher order synchronies, contain much information for the stimulus comparison in the hippocampal ca <dig> at the ensemble level.
information of the stimulus comparison may be distributed throughout the hippocampal ca1
to elucidate the decoding ability of small neuronal ensembles in the hippocampal ca <dig>  we examined the spatiotemporal firing patterns of small neuronal ensembles consisting of a maximum of  <dig> cells.
results of a previous study suggested that each of the discreetly located clusters of neurons is dedicated to a different aspect of the spatial version of the dnms task  <cit> .
therefore, not all represented information in the hippocampus might be induced from activity of the small neuronal ensembles detected in the present study.
that viewpoint, together with the results of analyses of firing rates of individual single cells  <cit> , suggests that larger neuronal ensembles in the hippocampus are associated with all examined events in addition to the stimulus comparison in the present study.
nevertheless, our results demonstrate that, in spite of using randomly selected neurons, all small neuronal ensembles in all the events we examined specifically classified the stimulus comparison.
for that reason, we infer that the information of stimulus comparison is not restricted, but is instead distributed throughout the hippocampal ca <dig>  it can be retrieved robustly by the ensemble activity of any subcombination in it.
on the other hand, in this study, the svm classifiers behave as the target of the hippocampal ca <dig>  such as the entorhinal cortex and subiculum.
those targets receive spikes not from the entire hippocampal ca <dig> but from a subset of it  <cit> .
consequently, the activity of a small neuronal ensemble in the hippocampal ca <dig> over brief time intervals during a single trial demonstrates the possibility that the targets of hippocampal ca <dig> work to perform, accurately, tasks that requires a stimulus comparison, as described in a recent study  <cit> .
CONCLUSIONS
the results show that a neuronal ensemble in the hippocampal ca <dig> acts as a comparator during a recognition memory task.
our approaches and findings revealed the cognitive functioning of the hippocampal ca <dig> from the neuronal ensemble activity in a single trial, supporting the development of new solutions for reading cognitive functions from the brain such as brain-machine interfaces  <cit> .
further assessment of the application of neuronal ensemble activity in the cognitive version of brain-machine interfaces can be achieved through experiments incorporating the sensory feedback of brain-controlled actuators in real-time.

 hippocampal formation has been identified as an important substrate for declarative memory for a broad range of materials in humans. in contrast, in rodent studies, two views respectively hold that the hippocampus is dedicated to spatial memory processing and that it associates general memory items. regarding the spatial view, results of several analyses of the stability of place cells have shown that pattern separation and pattern completion are apparent in neuronal ensembles of the hippocampus. in support of the general view, several experiments directly showed activity related to match/non-match conditions using recognition memory tasks, such as a delayed non-matching-to-sample task. spatial information can be regarded as multiple items that are mutually associated according to temporal relations. therefore, place cells might code multiple events constructing a place experienced in the past. from this viewpoint, the lines of evidence for the general and spatial views are not contradictory and are consistent with the view of the hippocampus as being capable of auto-associative functions to retrieve entire episodes. on the other hand, the matrix-like organization of the hippocampus with several inputs and outputs has inspired some researchers to propose the hippocampal comparator theory, which suggests that the hippocampus supports comparison, which might be one element in the match/non-match judgements. in this context, several lines of evidence obtained from analyses of single neurons in spatial and non-spatial behavioral tasks suggest that the hippocampus is critical for episodic-like representations. nevertheless, our knowledge related to neuronal computations in the working brain of behaving animals is limited; most of it has been inferred exclusively from changes in the firing rates of individual cells accumulated through many trials. therefore, to understand the hippocampal function completely, the actual encoding of information by the hippocampal neuronal networks of multiple neurons in a single trial during memory tasks must be elucidated. recently, some researchers have attempted to elucidate the functioning of neuronal networks of the cerebral cortex using an artificial neuronal network classifier as a decoder that enables us to analyze spatiotemporal firing patterns among all observed cells in a single trial. consequently, using multi-neuronal recording and an artificial neural network classifier as a decoder, we analyzed spatiotemporal firing patterns among cells in the hippocampal ca of rats. we report its neuronal ensemble code in a single trial of a dnms task.  we specifically examined the activities of the neuronal ensembles to provide quantitative constraints for hippocampal function. we used a decoding technique based on a linear classifier for neuronal ensembles. the decoding approach consists of training and regularizing a classifier to learn the map from neuronal ensemble activity to each behavioral label, as has been done similarly in recent studies of the inferior temporal and motor cortices. the classifier learns the map directly from the training sets and generalizes it to a novel ensemble activity instead of using prior knowledge of the probability distribution of the training sets. the input comprises neuronal ensemble activities from simultaneously monitored cells such as those shown in figures and after training a binary classifier using a leave-one-out cross-validation method, the classifier is useful to decode the ensemble activity in a novel trial of tasks. using such classifiers that can be implemented easily in neuronal networks of the hippocampal ca we can assess the lower bound on the information available in the ensemble activity in a single trial. classification performance in neuronal ensembles and combination we used the classifier approach to determine the functional roles of the ensembles of hippocampal ca during the dnms task. figure presents the cross-validated performance of the classifier for each neuronal ensemble. the spiking activity of the ensembles was sufficient to classify a match tone and non-match tone with maximum accuracy of 96% over a ms time interval. similarly, we determined the functional roles of the hippocampal ensembles in classifying go and non-go responses and high and low tones during sample and delay periods. the hippocampal ensembles were not capable of classifying these roles with sufficient accuracy. moreover, we compared correct and erroneous responses during the test periods, and low-test tone periods preceded by high sample tones and high test tone periods preceded by low sample tones. the results show that the hippocampal ensembles were also not capable of classifying these with significant accuracy. the performance values depicted in figure portray how accurately downstream neurons were able to classify the functional roles in a single trial, as determined using the computation of a weighted sum of spikes over a ms time interval. on the other hand, the classifier performance of the neuronal ensembles, as well as that of the combination, was enhanced approximately linearly with the logarithm of the number of participating cells, indicating that the codes for the stimulus comparison are distributed across cells, unlike that described by the grandmother cell doctrine. moreover, irrespective of the large number of cells in the combination, the accuracy of the combination was markedly lower than those of the ensembles over all the other examined time intervals. time resolution of code for stimulus comparison by investigating the degree to which classification performance depended on the bin size of the spike count, we examined the temporal resolution of the ensemble code. bin sizes of 2- ms yielded better performance than larger bin sizes. a 2-ms bin typically contained zero or one spike. consequently a few spikes from a small number of neurons are sufficient to encode the stimulus comparison in the hippocampal ensembles. discussion in this study, the activity of small neuronal ensembles in the hippocampal ca was used to classify the stimulus comparison with good accuracy over brief time intervals. they were not useful to classify the stimulus perception, stimulus retention, or motor selection. the accuracy of the ensembles for the stimulus comparison was markedly higher than that of the combination. small neuronal ensembles in the hippocampal ca specifically code stimulus comparison during test periods in which the rats prepare for go/no-go responses, we examined the stimulus comparison as well as the motor selection. the motor selection of go/no-go responses contains the stimulus comparison of match/non-match tones because, in correct trials, go and no-go responses respectively correspond to non-match and match tones. it is possible that the low accuracy of the ensembles for the motor selection suggest that the activities of the neuronal ensembles are not useful to classify the stimulus comparison. to verify the stimulus comparison without the influence of the motor functions, we examined ensemble activities during match and non-match tones to which identical behavioral responses were conducted. moreover, to exclude the influences of correct and erroneous responses and the particular stimuli being presented, we examined the classification performance of the ensemble activity in relation to the correct-error difference and the particular-stimulus presentation. the results show that, using a linear classifier that can be realized easily in downstream neurons by summating appropriately weighted inputs, we can clearly characterize that at the ensemble level, the most available information in the hippocampal ca in each single trial is specifically the stimulus comparison: it is neither the correct-error difference nor the particular-stimulus presentation. based on the results of ensemble analyses on a trial-to-trial basis, deadwyler and colleagues inferred multiple representation and conjunctive encoding in activities of small hippocampal ensembles consisting of neurons. in contrast with the present results, they showed that the stimulus comparison in the hippocampal ensembles was highly correlated with correct and erroneous responses. the reason for the inconsistent results might be differences in the tasks and differences in the ensemble analysis tools. furthermore, because we examined neuronal ensemble activities only in the hippocampal ca the activity of the hippocampal ca analyzed in the deadwyler's study might explain the inconsistency of the results. the results of the present study illustrate that small neuronal ensembles in the hippocampal ca are specifically dedicated to stimulus comparison. the results support the notion that the hippocampus contributes to memory by identifying consistencies across experiences that constitute new associations, as reported from some previous studies. the classification performance for the stimulus comparison of neuronal ensembles is better than that of their combination several lines of evidence suggested that firing rate modulations of individual neurons and spike timing among neurons contain information in the neuronal ensembles. given that the small neuronal ensembles in the hippocampal ca contains information related only to the firing rate modulations of individual neurons, the classification performance of the combination of all neurons in all the ensembles recorded from different sessions is expected to be the sum of the performance of the ensembles. however, in the present study, almost all classification performances of small neuronal ensembles in the hippocampal ca for the stimulus comparison were higher than that of the combination. moreover, the ensembles yielded better performance in a 2- ms window. from this perspective, we presume that the timing of spikes of 2- ms resolution in the ensembles recorded in the identical session, such as second or higher order synchronies, contain much information for the stimulus comparison in the hippocampal ca at the ensemble level. information of the stimulus comparison may be distributed throughout the hippocampal ca1 to elucidate the decoding ability of small neuronal ensembles in the hippocampal ca we examined the spatiotemporal firing patterns of small neuronal ensembles consisting of a maximum of cells. results of a previous study suggested that each of the discreetly located clusters of neurons is dedicated to a different aspect of the spatial version of the dnms task. therefore, not all represented information in the hippocampus might be induced from activity of the small neuronal ensembles detected in the present study. that viewpoint, together with the results of analyses of firing rates of individual single cells, suggests that larger neuronal ensembles in the hippocampus are associated with all examined events in addition to the stimulus comparison in the present study. nevertheless, our results demonstrate that, in spite of using randomly selected neurons, all small neuronal ensembles in all the events we examined specifically classified the stimulus comparison. for that reason, we infer that the information of stimulus comparison is not restricted, but is instead distributed throughout the hippocampal ca it can be retrieved robustly by the ensemble activity of any subcombination in it. on the other hand, in this study, the svm classifiers behave as the target of the hippocampal ca such as the entorhinal cortex and subiculum. those targets receive spikes not from the entire hippocampal ca but from a subset of it. consequently, the activity of a small neuronal ensemble in the hippocampal ca over brief time intervals during a single trial demonstrates the possibility that the targets of hippocampal ca work to perform, accurately, tasks that requires a stimulus comparison, as described in a recent study.  the results show that a neuronal ensemble in the hippocampal ca acts as a comparator during a recognition memory task. our approaches and findings revealed the cognitive functioning of the hippocampal ca from the neuronal ensemble activity in a single trial, supporting the development of new solutions for reading cognitive functions from the brain such as brain-machine interfaces. further assessment of the application of neuronal ensemble activity in the cognitive version of brain-machine interfaces can be achieved through experiments incorporating the sensory feedback of brain-controlled actuators in real-time. 
the role of neuronal ensembles in the hippocampal ca for a dnms task was assessed quantitatively in this study using multi-neuronal recordings and an artificial neural network classifier as a decoder. the activity of small neuronal ensembles over brief time intervals contains accurate information specifically related to the matching/non-matching of continuously presented stimuli. single-cell electrophysiological studies and studies of lesions or genetically altered animals using recognition memory tasks such as delayed non-matching-to-sample tasks support the theories. small neuronal networks in the hippocampal ca might therefore act as a comparator during recognition memory tasks. however, a complete understanding of hippocampal function necessitates knowledge of the encoding of information by multiple neurons in a single trial. the results show that the spatiotemporal patterns of spiking activity among cells in the small neuronal ensemble contain much information that is specifically useful for the stimulus comparison. the accuracy of the combination of neurons pooled over all the ensembles was markedly lower than those of the ensembles over all examined time intervals. the matrix-like organization of the hippocampus, with its several inputs and outputs, has given rise to several theories related to hippocampal information processing.
 the matrix-like organization of the hippocampus, with its several inputs and outputs, has given rise to several theories related to hippocampal information processing. single-cell electrophysiological studies and studies of lesions or genetically altered animals using recognition memory tasks such as delayed non-matching-to-sample tasks support the theories. however, a complete understanding of hippocampal function necessitates knowledge of the encoding of information by multiple neurons in a single trial. the role of neuronal ensembles in the hippocampal ca for a dnms task was assessed quantitatively in this study using multi-neuronal recordings and an artificial neural network classifier as a decoder.  the activity of small neuronal ensembles over brief time intervals contains accurate information specifically related to the matching/non-matching of continuously presented stimuli. the accuracy of the combination of neurons pooled over all the ensembles was markedly lower than those of the ensembles over all examined time intervals.  the results show that the spatiotemporal patterns of spiking activity among cells in the small neuronal ensemble contain much information that is specifically useful for the stimulus comparison. small neuronal networks in the hippocampal ca might therefore act as a comparator during recognition memory tasks. 