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Osamu Hoshino
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Journal Articles
Publisher: Journals Gateway
Neural Computation (2018) 30 (1): 184–215.
Published: 01 January 2018
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Learning of sensory cues is believed to rely on synchronous pre- and postsynaptic neuronal firing. Evidence is mounting that such synchronicity is not merely caused by properties of the underlying neuronal network but could also depend on the integrity of gap junctions that connect neurons and astrocytes in networks too. In this perspective, we set out to investigate the effect of astrocytic gap junctions on perceptual learning, introducing a model for coupled neuron-astrocyte networks. In particular, we focus on the fact that astrocytes are rich of GABA transporters (GATs) which can either uptake or release GABA depending on the astrocyte membrane potential, which is a function of local neural activity. We show that GABAergic signaling is a crucial component of intracolumnar neuronal synchronization, thereby promoting learning by neurons in the same cell assembly that are activated by a shared sensory cue. At the same time, we show that this effect can critically depend on astrocytic gap junctions insofar as these latter could synchronize extracellular GABA levels around many neurons and throughout entire cell assemblies. These results are supported by extensive computational arguments and predict that astrocytic gap junctions could improve perceptual learning by controlling extracellular GABA.
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Neural Computation (2016) 28 (1): 187–215.
Published: 01 January 2016
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Variability is a prominent characteristic of cognitive brain function. For instance, different trials of presentation of the same stimulus yield higher variability in its perception: subjects sometimes fail in perceiving the same stimulus. Perceptual variability could be attributable to ongoing-spontaneous fluctuation in neuronal activity prior to sensory stimulation. Simulating a cortical neural network model, we investigated the underlying neuronal mechanism of perceptual variability in relation to variability in ongoing-spontaneous neuronal activity. In the network model, populations of principal cells (cell assemblies) encode information about sensory features. Each cell assembly is sensitive to one particular feature stimulus. Transporters on GABAergic interneurons regulate ambient GABA concentration in a neuronal activity-dependent manner. Ambient GABA molecules activate extrasynaptic GABA receptors on principal cells and interneurons, and provide them with tonic inhibitory currents. We controlled the variability of ongoing-spontaneous neuronal activity by manipulating the basal level of ambient GABA and assessed the perceptual performance of the network: detection of a feature stimulus. In an erroneous response, stimulus-irrelevant but not stimulus-relevant principal cells were activated, generating trains of action potentials. Perceptual variability, reflected in error rate in detecting the same stimulus that was presented repeatedly to the network, was increased as the variability in ongoing-spontaneous membrane potential among cell assemblies increased. Frequent, transient membrane depolarization below firing threshold was the major cause of the increased neuronal variability, for which a decrease in basal ambient GABA concentration was responsible. We suggest that ambient GABA in the brain may have a role in reducing the variability in ongoing-spontaneous neuronal activity, leading to a decrease in perceptual variability and therefore to reliable sensory perception.
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Neural Computation (2015) 27 (6): 1223–1251.
Published: 01 June 2015
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Perception of supraliminal stimuli might in general be reflected in bursts of action potentials (spikes), and their memory traces could be formed through spike-timing-dependent plasticity (STDP). Memory traces for subliminal stimuli might be formed in a different manner, because subliminal stimulation evokes a fraction (but not a burst) of spikes. Simulations of a cortical neural network model showed that a subliminal stimulus that was too brief (10 msec) to perceive transiently (more than about 500 msec) depolarized stimulus-relevant principal cells and hyperpolarized stimulus-irrelevant principal cells in a subthreshold manner. This led to a small increase or decrease in ongoing-spontaneous spiking activity frequency (less than 1 Hz). Synaptic modification based on STDP during this period effectively enhanced relevant synaptic weights, by which subliminal learning was improved. GABA transporters on GABAergic interneurons modulated local levels of ambient GABA. Ambient GABA molecules acted on extrasynaptic receptors, provided principal cells with tonic inhibitory currents, and contributed to achieving the subthreshold neuronal state. We suggest that ongoing-spontaneous synaptic alteration through STDP following subliminal stimulation may be a possible neuronal mechanism for leaving its memory trace in cortical circuitry. Regulation of local ambient GABA levels by transporter-mediated GABA import and export may be crucial for subliminal learning.
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Neural Computation (2014) 26 (11): 2441–2464.
Published: 01 November 2014
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Default mode network (DMN) shows intrinsic, high-level activity at rest. We tested a hypothesis proposed for its role in sensory information processing: Intrinsic DMN activity facilitates neural responses to sensory input. A neural network model, consisting of a sensory network (Nsen) and a DMN, was simulated. The Nsen contained cell assemblies. Each cell assembly comprised principal cells, GABAergic interneurons (Ia, Ib), and glial cells. We let the Nsen carry out a perceptual task: detection of sensory stimuli. During DMN activation, glial cells were hyperpolarized by Ia-to-glia circuitry, by which glial membrane transporters imported GABA molecules from the extracellular space and decreased ambient GABA concentration. Acting on extrasynaptic GABA receptors, the decrease in ambient GABA concentration reduced inhibitory current in a tonic manner. This depolarized principal cells below their firing threshold during the ongoing spontaneous time period and accelerated their reaction speed to a sensory stimulus. During the stimulus presentation period, the Nsen inhibited the DMN and caused DMN deactivation. The DMN deactivation made Nsen Ia cells cease firing, thereby stopping the glial membrane hyperpolarization, quitting the GABA import, returning to the basal ambient GABA level, and thus enhancing global inhibition. Notably, the stimulus-relevant P cell firing could be maintained when GABAergic gliotransmission via Ia-glia signaling worked, decreasing ambient GABA concentration around the stimulus-relevant P cells. This enabled the Nsen to reliably detect the stimulus. We suggest that intrinsic default model network activity may accelerate the reaction speed of the sensory network by modulating its ongoing-spontaneous activity in a subthreshold manner. Ambient GABA contributes to achieve an optimal ongoing spontaneous subthreshold neuronal state, in which GABAergic gliotransmission triggered by the intrinsic default model network activity may play an important role.
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Neural Computation (2014) 26 (8): 1690–1716.
Published: 01 August 2014
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For sensory cortices to respond reliably to feature stimuli, the balancing of neuronal excitation and inhibition is crucial. A typical example might be the balancing of phasic excitation within cell assemblies and phasic inhibition between cell assemblies. The former controls the gain of and the latter the tuning of neuronal responses. A change in ambient GABA concentration might affect the dynamic behavior of neurons in a tonic manner. For instance, an increase in ambient GABA concentration enhances the activation of extrasynaptic receptors, augments an inhibitory current, and thus inhibits neurons. When a decrease in ambient GABA concentration occurs, the tonic inhibitory current is reduced, and thus the neurons are relatively excited. We simulated a neural network model in order to examine whether and how such a tonic excitatory-inhibitory mechanism could work for sensory information processing. The network consists of cell assemblies. Each cell assembly, comprising principal cells (P), GABAergic interneurons (Ia, Ib), and glial cells (glia), responds to one particular feature stimulus. GABA transporters, embedded in glial plasma membranes, regulate ambient GABA levels. Hypothetical neuron-glia signaling via inhibitory (Ia-to-glia) and excitatory (P-to-glia) synaptic contacts was assumed. The former let transporters import (remove) GABA from the extracellular space and excited stimulus-relevant P cells. The latter let them export GABA into the extracellular space and inhibited stimulus-irrelevant P cells. The main finding was that the glial membrane transporter gave a combinatorial excitatory-inhibitory effect on P cells in a tonic manner, thereby improving the gain and tuning of neuronal responses. Interestingly, it worked cooperatively with the conventional, phasic excitatory-inhibitory mechanism. We suggest that the GABAergic gliotransmission mechanism may provide balanced intracortical excitation and inhibition so that the best perceptual performance of the cortex can be achieved.
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Neural Computation (2014) 26 (7): 1362–1385.
Published: 01 July 2014
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We examined whether and how the balancing of crossmodal excitation and inhibition affects intersensory facilitation. A neural network model, comprising lower-order unimodal networks (X, Y) and a higher-order multimodal network (M), was simulated. Crossmodal excitation was made by direct activation of principal cells of the X network by the Y network. Crossmodal inhibition was made in an indirect manner: the Y network activated glial cells of the X network. This let glial plasma membrane transporters export GABA molecules into the extracellular space and increased the level of ambient GABA. The ambient GABA molecules were accepted by extrasynaptic GABA a receptors and tonically inhibited principal cells of the X network. Namely, crossmodal inhibition was made through GABAergic gliotransmission. Intersensory facilitation was assessed in terms of multisensory gain: the difference between the numbers of spikes evoked by multisensory (XY) stimulation and unisensory (X-alone) stimulation. The maximal multisensory gain (XY-X) could be achieved at an intermediate noise level by balancing crossmodal excitation and inhibition. This result supports an experimentally derived conclusion: intersensory facilitation under noisy environmental conditions is not necessarily in accord with the principle of inverse effectiveness; rather, multisensory gain is maximal at intermediate signal-to-noise ratio (SNR) levels. The maximal multisensory gain was available at the weakest signal if noise was not present, indicating that the principle of inverse effectiveness is a special case of the intersensory facilitation model proposed here. We suggest that the balancing of crossmodal excitation and inhibition may be crucial for intersensory facilitation. The GABAergic glio-transmission-mediated crossmodal inhibitory mechanism effectively works for intersensory facilitation and on determining the maximal multisensory gain in the entire SNR range between the two extremes: low and high SNRs.
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Neural Computation (2013) 25 (12): 3235–3262.
Published: 01 December 2013
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We examined how the depression of intracortical inhibition due to a reduction in ambient GABA concentration impairs perceptual information processing in schizophrenia. A neural network model with a gliotransmission-mediated ambient GABA regulatory mechanism was simulated. In the network, interneuron-to-glial-cell and principal-cell-to-glial-cell synaptic contacts were made. The former hyperpolarized glial cells and let their transporters import (remove) GABA from the extracellular space, thereby lowering ambient GABA concentration, reducing extrasynaptic GABA a receptor-mediated tonic inhibitory current, and thus exciting principal cells. In contrast, the latter depolarized the glial cells and let the transporters export GABA into the extracellular space, thereby elevating the ambient GABA concentration and thus inhibiting the principal cells. A reduction in ambient GABA concentration was assumed for a schizophrenia network. Multiple dynamic cell assemblies were organized as sensory feature columns. Each cell assembly responded to one specific feature stimulus. The tuning performance of the network to an applied feature stimulus was evaluated in relation to the level of ambient GABA. Transporter-deficient glial cells caused a deficit in GABAergic gliotransmission and reduced ambient GABA concentration, which markedly deteriorated the tuning performance of the network, broadening the sensory tuning. Interestingly, the GABAergic gliotransmission mechanism could regulate local ambient GABA levels: it augmented ambient GABA around stimulus-irrelevant principal cells, while reducing ambient GABA around stimulus-relevant principal cells, thereby ensuring their selective responsiveness to the applied stimulus. We suggest that a deficit in GABAergic gliotransmission may cause a reduction in ambient GABA concentration, leading to a broadening of sensory tuning in schizophrenia. The GABAergic gliotransmission mechanism proposed here may have an important role in the regulation of local ambient GABA levels, thereby improving the sensory tuning performance of the cortex.
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Neural Computation (2013) 25 (5): 1164–1190.
Published: 01 May 2013
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Multistable perception is a psychophysical phenomenon in which one unique interpretation alternates spontaneously every few seconds between two or more interpretations of the same sensory input. Well-known examples include the Necker cube and face-vase illusions in vision. Interestingly, young adults generally see more perceptual switches than do elderly people. To understand the underlying neuronal mechanism of age-related multistable perception, we simulated a cortical neural network model that consists of multiple cell assemblies. In the network, a specific population of noncore cells and a common population of core cells form a cell assembly that represents a single object (or event). Every dynamic cell assembly, activated by a given sensory input, involves the common (overlapping) population of core cells. Ambient GABA-mediated intracortical tonic inhibition via extrasynaptic GABA a receptors destabilized the currently appearing dynamic cell assembly and terminated its burst firing. This allowed another dynamic cell assembly to emerge one after the other. Namely, multistable perception took place. Transporters, which were embedded in axon terminal membranes of interneurons, regulated levels of ambient GABA. For elderly people, we assumed a decline in transporter. This decelerated GABA augmentation and resulted in prolonging the durations of burst firing and thus in slowing perceptual switches. We suggest that poor control of ambient GABA levels due to age-related decline in GABA transporter may be responsible for the slowing of perceptual switches in elderly people.
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Neural Computation (2012) 24 (11): 2964–2993.
Published: 01 November 2012
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Activities of sensory-specific cortices are known to be suppressed when presented with a different sensory modality stimulus. This is referred to as cross-modal inhibition, for which the conventional synaptic mechanism is unlikely to work. Interestingly, the cross-modal inhibition could be eliminated when presented with multisensory stimuli arising from the same event. To elucidate the underlying neuronal mechanism of cross-modal inhibition and understand its significance for multisensory information processing, we simulated a neural network model. Principal cell to and GABAergic interneuron to glial cell projections were assumed between and within lower-order unimodal networks (X and Y), respectively. Cross-modality stimulation of Y network activated its principal cells, which then depolarized glial cells of X network. This let transporters on the glial cells export GABA molecules into the extracellular space and increased a level of ambient (extrasynaptic) GABA. The ambient GABA molecules were accepted by extrasynaptic GABA a receptors and tonically inhibited principal cells of the X network. Cross-modal inhibition took place in a nonsynaptic manner. Identical modality stimulation of X network activated its principal cells, which then activated interneurons and hyperpolarized glial cells of the X network. This let their transporters import (remove) GABA molecules from the extracellular space and reduced tonic inhibitory current in principal cells, thereby improving their gain function. Top-down signals from a higher-order multimodal network (M) contributed to elimination of the cross-modal inhibition when presented with multisensory stimuli that arose from the same event. Tuning into the multisensory event deteriorated if the cross-modal inhibitory mechanism did not work. We suggest that neuron-glia signaling may regulate local ambient GABA levels in order to coordinate cross-modal inhibition and improve neuronal gain function, thereby achieving reliable perception of multisensory events.
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Neural Computation (2012) 24 (3): 744–770.
Published: 01 March 2012
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In visual information processing, feedforward projection from primary to secondary visual cortex (V1-to-V2) is essential for integrating combinations of oriented bars in order to extract angular information embedded within contours that represent the shape of objects. For feedback (V2-to-V1) projection, two distinct types of pathways have been observed: clustered projection and diffused projection. The former innervates V1 domains with a preferred orientation similar to that of V2 cells of origin. In contrast, the latter innervates without such orientation specificity. V2 cells send their axons to V1 domains with both similar and dissimilar orientation preferences. It is speculated that the clustered feedback projection has a role in contour integration. The role of the diffused feedback projection, however, remains to be seen. We simulated a minimal, functional V1-V2 neural network model. The diffused feedback projection contributed to achieving ongoing-spontaneous subthreshold membrane oscillations in V1 cells, thereby reducing the reaction time of V1 cells to a pair of bars that represents specific angular information. Interestingly, the feedback influence took place even before V2 responses, which might stem largely from ongoing-spontaneous signaling from V2. We suggest that the diffusive feedback influence from V2 could act early in V1 responses and accelerate their reaction speed to sensory stimulation in order to rapidly extract angular information.
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Neural Computation (2011) 23 (12): 3205–3231.
Published: 01 December 2011
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Experience-dependent synaptic plasticity characterizes the adaptable brain and is believed to be the cellular substrate for perceptual learning. A chemical agent such as gamma-aminobutyric acid (GABA) is known to affect synaptic alteration, perhaps gating perceptual learning. We examined whether and how ambient (extrasynaptic) GABA affects experience-dependent synaptic alteration. A cortical neural network model was simulated. Transporters on GABAergic interneurons regulate ambient GABA levels around their axonal target neurons by removing GABA from (forward transport) or releasing it into (reverse transport) the extracellular space. The ambient GABA provides neurons with tonic inhibitory currents by activating extrasynaptic GABA a receptors. During repeated exposures to the same stimulus, we modified the synaptic connection strength between principal cells in a spike-timing-dependent manner. This modulated the activity of GABAergic interneurons, and reduced or augmented ambient GABA concentration. Reduction in ambient GABA concentration led to slight depolarization (less than several millivolts) in ongoing-spontaneous membrane potential. This was a subthreshold neuronal behavior because ongoing-spontaneous spiking activity remained almost unchanged. The ongoing-spontaneous subthreshold depolarization improved a suprathreshold neuronal response. If the stimulus was long absent for perceptual learning, augmentation of ambient GABA concentration took place and the ongoing-spontaneous subthreshold depolarization was depressed. We suggest that a perceptual memory trace could be left in neuronal circuitry as an ongoing-spontaneous subthreshold membrane depolarization, which would allow that memory to be accessed easily afterward, whereas a trace of a memory that has not recently been retrieved fades away when the ongoing-spontaneous subthreshold membrane depolarization built by previous perceptual learning is depressed. This would lead that memory to be accessed with some difficulty. In the brain, ambient GABA, whose level could be regulated by transporter may have an important role in leaving memory trace for perceptual learning.
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Neural Computation (2011) 23 (4): 958–983.
Published: 01 April 2011
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Multisensory integration (such as somatosensation-vision, gustation-olfaction) could occur even between subthreshold stimuli that in isolation do not reach perceptual awareness. For example, when a somatosensory (subthreshold) stimulus is delivered within a close spatiotemporal congruency, a visual (subthreshold) stimulus evokes a visual percept. Cross-modal enhancement of visual perception is maximal when the somatosensory stimulation precedes the visual one by tens of milliseconds. This rapid modulatory response would not be consistent with a top-down mechanism acting through higher-order multimodal cortical areas, but rather a direct interaction between lower-order unimodal areas. To elucidate the neuronal mechanisms of subthreshold cross-modal enhancement, we simulated a neural network model. In the model, lower unimodal (X, Y) and higher multimodal (M) networks are reciprocally connected by bottom-up and top-down axonal projections. The lower networks are laterally connected with each other. A pair of stimuli was presented to the lower networks, whose respective intensities were too weak to induce salient neuronal activity (population response) when presented alone. Neurons of the Y network were slightly depolarized below firing threshold when a cross-modal stimulus was presented alone to the X network. This allowed the Y network to make a rapid (within tens of milliseconds) population response when presented with a subsequent congruent stimulus. The reaction speed of the Y network was accelerated, provided that the top-down projections were strengthened. We suggest that a subthreshold (nonpopulation) response to a cross-modal stimulus, acting through interaction between lower (primary unisensory) areas, may be essential for a rapid suprathreshold (population) response to a congruent stimulus that follows. Top-down influences on cross-modal enhancement may be faster than expected, accelerating reaction speed to input, in which ongoing-spontaneous subthreshold excitation of lower-order unimodal cells by higher-order multimodal cells may play an active role.
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Neural Computation (2010) 22 (5): 1358–1382.
Published: 01 May 2010
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Neurons of primary auditory cortex (AI) emit spikes (action potentials) in two distinct manners, responding to sounds in an onset or a sustained manner. The former AI neurons are called phasic cells and the latter tonic cells. The phasic cells generate spikes for a brief time period (less than hundreds of milliseconds) at the onset of an auditory stimulus (e.g., a tone frequency sound), and the tonic cells continuously generate spikes throughout the stimulation period. Simulating a neural network model of AI, we investigated whether and how the onset discharges influence the sustained discharges that are believed to play a central role in encoding auditory information. Onset discharges, triggered by a phasic input, briefly excited GABAergic interneurons and transiently increased the level of ambient GABA, which was immediately recognized by extrasynaptic GABA a receptors and provided inhibitory currents into neurons. The transient alteration of ambient GABA allowed tonic cells to respond selectively to a tonic input. The timing of phasic input relative to a tonic one had a great impact on the responsiveness of tonic cells. We found optimal timing for the best selective responsiveness: phasic input preceding tonic input by several tens of milliseconds. Offset discharges induced by a secondary input to phasic cells, applied at the end of the tonic input period, suddenly terminated the sustained discharges and allowed the network to return rapidly to the ongoing-spontaneous neuronal state. We suggest that the transporter-mediated alteration of ambient GABA, triggered by onset discharges, may improve the response property of AI neurons. Offset discharges may have a role in resetting AI neurons so that they can prepare for the next auditory input.
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Neural Computation (2009) 21 (6): 1683–1713.
Published: 01 June 2009
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There has been compelling evidence that the GABA transporter is crucial not only for removing gamma-aminobutyric acid (GABA) from but also releasing it into extracellular space, thereby clamping ambient GABA (GABA in extracellular space) at a certain level. The ambient GABA is known to activate extrasynaptic GABA receptors and provide tonic inhibitory current into neurons. We investigated how the transporter regulates the level of ambient GABA, mediates tonic neuronal inhibition, and influences ongoing spontaneous neuronal activity. A cortical neural network model is proposed in which GABA transporters on lateral (L) and feedback (F) inhibitory (GABAergic) interneurons are functionally made. Principal (P) cell assemblies participate in expressing information about elemental sensory features. At membrane potentials below the reversal potential, there is net influx of GABA, whereas at membrane potentials above the reversal potential, there is net efflux of GABA. Through this transport mechanism, ambient GABA concentration is kept within a submicromolar range during an ongoing spontaneous neuronal activity time period. Here we show that the GABA transporter on L cells regulates the overall level of ambient GABA across cell assemblies, and that on F cells it does so within individual cell assemblies. This combinatorial regulation of ambient GABA allows P cells to oscillate near firing threshold during the ongoing time period, thereby reducing their reaction time to externally applied stimuli. We suggest that the GABA transporter, with its forward and reverse transport mechanism, could regulate the ambient GABA. This transporter-mediated ambient GABA regulation may contribute to establishing an ongoing subthreshold neuronal state by which the network can respond rapidly to subsequent sensory input.
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Neural Computation (2008) 20 (12): 3055–3086.
Published: 01 December 2008
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Ensemble activation of neurons, triggered or spontaneous, sometimes involves a common (overlapping) neuronal population known as core cells. It is speculated that the core cells functioning as a core nucleus have a role in dictating noncore cells' behavior and thus overall local network dynamics. However, the truth and its significance in neuronal information processing still remain to be seen. To address this issue, a neural network model of an early sensory cortical area was simulated. In the network model, noncore cells that have selective responsiveness to sensory features constituted noncore cell assemblies. Core cells, having unselective responsiveness, constituted a single core cell assembly. Sensory stimulation activated neuronal ensembles that were indistinguishable from those activated spontaneously. The core cells were active in every ensemble activation and recruited a changing complement of noncore cells, which varied from spontaneous event to spontaneous event or from triggered event to triggered event. Ensemble activation of neurons was established through what we call dynamic coassembling, in which the core cell assembly and one of the noncore cell assemblies were dynamically linked together. Transient dynamic coassembling frequently and randomly took place during the ongoing (spontaneous) neuronal activity period, and persistent dynamic coassembling did during the stimulus-triggered neuronal activity period. The frequent ongoing activation of core cells mediated through transient dynamic coassembling depolarized noncore cells just below firing threshold, whereby the noncore cells could respond rapidly to sensory stimulation. The persistent dynamic coassembling enhanced the responsiveness of noncore cells. We suggest that the core cells, functioning as a core nucleus, dictate how the noncore cells oscillate at a subthreshold level during the ongoing period and how to respond when stimulated. The transient and persistent dynamic coassembling may be an essential neuronal mechanism for the cortex to prepare and respond effectively to sensory input.
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Neural Computation (2007) 19 (12): 3310–3334.
Published: 01 December 2007
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Accumulating evidence suggests that auditory cortical neurons exhibit widespread-onset responses and restricted sustained responses to sound stimuli. When a sound stimulus is presented to a subject, the auditory cortex first responds with transient discharges across a relatively large population of neurons, showing widespread-onset responses. As time passes, the activation becomes restricted to a small population of neurons that are preferentially driven by the stimulus, showing restricted sustained responses. The sustained responses are considered to have a role in expressing information about the stimulus, but it remains to be seen what roles the widespread-onset responses have in auditory information processing. We carried out numerical simulations of a neural network model for a lateral belt area of auditory cortex. In the network, dynamic cell assemblies expressed information about auditory sounds. Lateral excitatory and inhibitory connections were made between cell assemblies, respectively, by direct and indirect projections via interneurons. Widespread-onset neuronal responses to sound stimuli (bandpassed noises) took place over the network if lateral excitation preceded lateral inhibition, making a time widow for the onset responses. The widespread-onset responses contributed to the accelerating reaction time of neurons to sensory stimulation. Lateral interaction among dynamic cell assemblies was essential for maintaining ongoing membrane potentials near thresholds for action potential generation, thereby accelerating reaction time to subsequent sensory input as well. We suggest that the widespread-onset neuronal responses and the ongoing subthreshold cortical state, for which the coordination of lateral synaptic interaction among dissimilar cell assemblies is essential, may work together in order for the auditory cortex to quickly detect the sudden occurrence of sounds from the external environment.
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Neural Computation (2007) 19 (2): 351–370.
Published: 01 February 2007
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Auditory communication signals such as monkey calls are complex FM vocal sounds and in general induce action potentials in different timing in the primary auditory cortex. Delay line scheme is one of the effective ways for detecting such neuronal timing. However, the scheme is not straightforwardly applicable if the time intervals of signals are beyond the latency time of delay lines. In fact, monkey calls are often expressed in longer time intervals (hundreds of milliseconds to seconds) and are beyond the latency times observed in the brain (less than several hundreds of milliseconds). Here, we propose a cochleotopic map similar to that in vision known as a retinotopic map. We show that information about monkey calls could be mapped on a cochleotopic cortical network as spatiotemporal firing patterns of neurons, which can then be decomposed into simple (linearly sweeping) FM components and integrated into unified percepts by higher cortical networks. We suggest that the spatiotemporal conversion of auditory information may be essential for developing the cochleotopic map, which could serve as the foundation for later processing, or monkey call identification by higher cortical areas.
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Neural Computation (2005) 17 (8): 1739–1775.
Published: 01 August 2005
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We propose two distinct types of norepinephrine (NE)-neuromodulatory systems: an enhanced-excitatory and enhanced-inhibitory (E-E/E-I) system and a depressed-excitatory and enhanced-inhibitory (D-E/E-I) system. In both systems, inhibitory synaptic efficacies are enhanced, but excitatory ones are modified in a contradictory manner: the E-E/E-I system enhances excitatory synaptic efficacies, whereas the D-E/E-I system depresses them. The E-E/E-I and D-E/E-I systems altered the dynamic property of ongoing (background) neuronal activity and greatly influenced the cognitive performance (S/N ratio) of a cortical neural network. The E-E/E-I system effectively enhanced S/N ratio for weaker stimuli with lower doses of NE, whereas the D-E/E-I system enhanced stronger stimuli with higher doses of NE. The neural network effectively responded to weaker stimuli if brief γ-bursts were involved in ongoing neuronal activity that is controlled under the E-E/E-I neuromodulatory system. If the E-E/E-I and the D-E/E-I systems interact within the neural network, depressed neurons whose activity is depressed by NE application have bimodal property. That is, S/N ratio can be enhanced not only for stronger stimuli as its original property but also for weaker stimuli, for which coincidental neuronal firings among enhanced neurons whose activity is enhanced by NE application are essential. We suggest that the recruitment of the depressed neurons for the detection of weaker (subthreshold) stimuli might be advantageous for the brain to cope with a variety of sensory stimuli.
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Neural Computation (2004) 16 (3): 563–594.
Published: 01 March 2004
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Our ability to perceive external sensory stimuli improves as we experience the same stimulus repeatedly. This perceptual enhancement, called perceptual learning , has been demonstrated for various sensory systems, such as vision, audition, and somatosensation. I investigated the contribution of lateral excitatory and inhibitory synaptic balance to perceptual learning. I constructed a simple associative neural network model in which sensory features were expressed by the activities of specific cell assemblies. Each neuron is sensitive to a specific sensory feature, and the neurons belonging to the same cell assembly are sensitive to the same feature. During perceptual learning processes, the network was presented repeatedly with a stimulus that was composed of a sensory feature and noise, and the lateral excitatory and inhibitory synaptic connection strengths between neurons were modified according to a pulse-timing-based Hebbian rule. Perceptual learning enhanced the cognitive performance of the network, increasing the signal-to-noise ratio of neuronal activity. I suggest here that the alteration of the synaptic balance may be essential for perceptual learning, especially when the brain tries to adopt the most suitable strategy—signal enhancement, noise reduction, or both—for a given perceptual task.
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Neural Computation (2001) 13 (8): 1781–1810.
Published: 01 August 2001
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A hierarchical dynamical map is proposed as the basic framework for sensory cortical mapping. To show how the hierarchical dynamical map works in cognitive processes, we applied it to a typical cognitive task known as priming, in which cognitive performance is facilitated as a consequence of prior experience. Prior to the priming task, the network memorizes a sensory scene containing multiple objects presented simultaneously using a hierarchical dynamical map. Each object is composed of different sensory features. The hierarchical dynamical map presented here is formed by random itinerancy among limit-cycle attractors into which these objects are encoded. Each limit-cycle attractor contains multiple point attractors into which elemental features belonging to the same object are encoded. When a feature stimulus is presented as a priming cue, the network state is changed from the itinerant state to a limit-cycle attractor relevant to the priming cue. After a short priming period, the network state reverts to the itinerant state. Under application of the test cue, consisting of some feature belonging to the object relevant to the priming cue and fragments of features belonging to others, the network state is changed to a limit-cycle attractor and finally to a point attractor relevant to the target feature. This process is considered as the identification of the target. The model consistently reproduces various observed results for priming processes such as the difference in identification time between cross-modality and within-modality priming tasks, the effect of interval between priming cue and test cue on identification time, the effect of priming duration on the time, and the effect of repetition of the same priming task on neural activity.