Minoru Tsukada

Neural Correlates of True Memory, False Memory, and Deception

We used functional magnetic resonance imaging (fMRI) to determine whether neural activity can differentiate between true memory, false memory, and deception. Subjects heard a series of semantically related words and were later asked to make a recognition judgment of old words, semantically related nonstudied words (lures for false recognition), and unrelated new words. They were also asked to make a deceptive response to half of the old and unrelated new words. There were 3 main findings. First, consistent with the notion that executive function supports deception, 2 types of deception (pretending to know and pretending not to know) recruited prefrontal activity. Second, consistent with the sensory reactivation hypothesis, the difference between true recognition and false recognition was found in the left temporoparietal regions probably engaged in the encoding of auditorily presented words. Third, the left prefrontal cortex was activated during pretending to know relative to correct rejection and false recognition, whereas the right anterior hippocampus was activated during false recognition relative to correct rejection and pretending to know. These findings indicate that fMRI can detect the difference in brain activity between deception and false memory despite the fact that subjects respond with “I know” to novel events in both processes.

Prototypic Seizure Activity Driven by Mature Hippocampal Fast-Spiking Interneurons

A variety of epileptic seizure models have shown that activation of glutamatergic pyramidal cells is usually required for rhythm generation and/or synchronization in hippocampal seizure-like oscillations in vitro. However, it still remains unclear whether GABAergic interneurons may be able to drive the seizure-like oscillations without glutamatergic transmission. Here, we found that electrical stimulation in rat hippocampal CA1 slices induced a putative prototype of seizure-like oscillations (“prototypic afterdischarge,” 1.8–3.8 Hz) in mature pyramidal cells and interneurons in the presence of ionotropic glutamate receptor antagonists. The prototypic afterdischarge was abolished by GABAA receptor antagonists or gap junction blockers, but not by a metabotropic glutamate receptor antagonist or a GABAB receptor antagonist. Gramicidin-perforated patch-clamp and voltage-clamp recordings revealed that pyramidal cells were depolarized and frequently excited directly through excitatory GABAergic transmissions in each cycle of the prototypic afterdischarge. Interneurons that were actively spiking during the prototypic afterdischarge were mostly fast-spiking (FS) interneurons located in the strata oriens and pyramidale. Morphologically, these interneurons that might be “potential seizure drivers” included basket, chandelier, and bistratified cells. Furthermore, they received direct excitatory GABAergic input during the prototypic afterdischarge. The O-LM cells and most of the interneurons in the strata radiatum and lacunosum moleculare were not essential for the generation of prototypic afterdischarge. The GABA-mediated prototypic afterdischarge was observed later than the third postnatal week in the rat hippocampus. Our results suggest that an FS interneuron network alone can drive the prototypic form of electrically induced seizure-like oscillations through their excitatory GABAergic transmissions and presumably through gap junction-mediated communications.

Reward prediction based on stimulus categorization in primate lateral prefrontal cortex

To adapt to changeable or unfamiliar environments, it is important that animals develop strategies for goal-directed behaviors that meet the new challenges. We used a sequential paired-association task with asymmetric reward schedule to investigate how prefrontal neurons integrate multiple already-acquired associations to predict reward. Two types of reward-related neurons were observed in the lateral prefrontal cortex: one type predicted reward independent of physical properties of visual stimuli and the other encoded the reward value specific to a category of stimuli defined by the task requirements. Neurons of the latter type were able to predict reward on the basis of stimuli that had not yet been associated with reward, provided that another stimulus from the same category was paired with reward. The results suggest that prefrontal neurons can represent reward information on the basis of category and propagate this information to category members that have not been linked directly with any experience of reward.

Hippocampal LTP depends on spatial and temporal correlation of inputs

We studied the LTP inducing factors using temporally and spatially modulated stimuli given to the hippocampal neural network. It was found that when the spatial factors were maintained to be constant the positive correlation in the successive inter-stimulus intervals contributes to produce larger LTP. On the other hand, if the temporal factors are kept constant, the spatial coincidence contributes to produce larger LTP. We propose a learning rule by which these experimental results can be consistently interpreted. Copyright 1996 Elsevier Science Ltd.

THEORETICAL MODEL OF THE HIPPOCAMPAL-CORTICAL MEMORY SYSTEM MOTIVATED BY PHYSIOLOGICAL FUNCTIONS IN THE HIPPOCAMPUS

Electrical stimulation in the hippocampus leads to an increase in synaptic efficacy that lasts for many hours. This long-term potentiation (LTP) of synaptic transmission is presumed to play a crucial role in learning and memory in the brain. Our experimental data on the hippocampus show that the homosynaptic LTP and the associative LTP are highly sensitive to temporal pattern stimuli given by different correlations between successive interstimulus events, even when the mean rate of the stimuli is held constant; negatively correlated stimuli have relatively little LTP, whereas positively correlated stimuli have greater LTP. This suggests that the detailed temporal properties of the stimulus are an important factor in inducing LTP and supports the possibility that temporal codes are used as indexes in associating/dissociating memory events in the hippocampus. Based on the physiological evidence, we propose a hypothesis on how association and dissociation of event memories are done in the hippocampal-cortica...

The spatiotemporal learning rule and its efficiency in separating spatiotemporal patterns

The hippocampus plays an important role in the course of establishing long-term memory, i.e., to make short-term memory of spatially and temporally associated input information. In 1996 (Tsukada et al. 1996), the spatiotemporal learning rule was proposed based on differences observed in hippocampal long-term potentiation (LTP) induced by various spatiotemporal pattern stimuli. One essential point of this learning rule is that the change of synaptic weight depends on both spatial coincidence and the temporal summation of input pulses. We applied this rule to a single-layered neural network and compared its ability to separate spatiotemporal patterns with that of other rules, including the Hebbian learning rule and its extended rules. The simulated results showed that the spatiotemporal learning rule had the highest efficiency in discriminating spatiotemporal pattern sequences, while the Hebbian learning rule (including its extended rules) was sensitive to differences in spatial patterns.

Cholinergic modulation on spike timing-dependent plasticity in hippocampal CA1 network

Cholinergic inputs from the medial septum are projected to pyramidal neurons in the hippocampal CA1 region and release acetylcholine (ACh) from their terminals. The cholinergic inputs are considered to be integrated with sensory inputs and to play a crucial role in learning and memory. Meanwhile, it has been reported that the relative timing between pre- and post-synaptic spiking determines the direction and extent of synaptic changes in a critical temporal window, a process known as spike timing-dependent plasticity (STDP). Positive timing where excitatory postsynaptic potential (EPSP) precedes the postsynaptic action potential induces long-term potentiation (LTP) while negative timing where EPSP follows the action potential induces long-term depression (LTD). To investigate the influence of muscarinic activation by cholinergic inputs on synaptic plasticity, STDP-inducing stimuli were applied during the muscarinic induction of a slow EPSP followed by repetitive stimulation in the stratum oriens. As a result, LTP was facilitated and LTD was abolished by the muscarinic activation. Furthermore, interestingly, LTP was also facilitated and LTD was switched to LTP with an increase in ACh concentration following application of the cholinesterase inhibitor eserine. These results indicate that the orientation of plasticity was shifted for potentiation by muscarinic activation. On the other hand, the application of excess ACh concentration completely suppressed STDP, LTP and LTD. In addition, STDP was suppressed in the presence of atropine, a muscarinic ACh receptor antagonist. Taken together, the findings suggest that synaptic plasticity modulation depends on the amount of cholinergic inputs. The modulation of synaptic plasticity by muscarinic activation might be an important stage in the integration of top-down and bottom-up information in hippocampal CA1 neurons.

Classification of neuronal activities from tetrode recordings using independent component analysis

Abstract Classifying spike shapes in multi-unit recordings has been important to extract single neuronal activities from nervous tissue. Although several methods for this purpose have been developed, most of them have had limitations in their ability to decompose single unit activities. When more than two neurons generate action potentials simultaneously, it is difficult to identify the spikes because of the overlap of the spike waveforms. In this paper, we suggest a procedure that solves this problem using independent component analysis. By testing for the refractory period of spikes in each independent component, the proposed procedure is efficient for the decomposition of neuronal activities.

Interaction between the SpatioTemporal Learning Rule (STLR) and Hebb type (HEBB) in single pyramidal cells in the hippocampal CA1 Area

The spatiotemporal learning rule (STLR), proposed as a non-Hebb type by Tsukada et al. (Neural Networks 9 (1996) 1357 and Tsukada and Pan (Biol. cyberm 92 (2005) 139), 2005), consists of two distinctive factors; “cooperative plasticity without a cell spike,” and “its temporal summation”. On the other hand, Hebb (The organization of behavior. John Wiley, New York, 1949) proposed the idea (HEBB) that synaptic modification is strengthened only if the pre- and post-cell are activated simultaneously. We have shown, experimentally, that both STLR and HEBB coexist in single pyramidal cells of the hippocampal CA1 area. The functional differences between STLR and HEBB in dendrite (local)-soma (global) interactions in single pyramidal cells of CA1 and the possibility of pattern separation, pattern completion and reinforcement learning were discussed.

Stimulus-dependent induction of long-term potentiation in CA1 area of the hippocampus: experiment and model.

In the CA1 area of the hippocampus, the magnitude of long‐term potentiation (LTP) depends not only on the frequency of applied stimuli, but also on their number. With a slice preparation using extracellular recording in the hippocampus CA1 of a guinea pig, we investigate the magnitude of LTP induced by electrical stimuli with a range of frequencies and the number of applied stimuli. We find that the magnitude of the saturated potentiation obtained with periodic stimuli largely depends on the frequency and is insensitive to the number of stimuli, once the saturation level has been obtained. Furthermore, we investigated nonperiodic stimuli and found that the magnitude of the saturated potentiation is also sensitive to the statistical correlation between successive interstimulus intervals, even when their average frequency is held constant.