Deciphering Elapsed Time and Predicting Action Timing from Neuronal Population Signals

The proper timing of actions is necessary for the survival of animals, whether in hunting prey or escaping predators. Researchers in the field of neuroscience have begun to explore neuronal signals correlated to behavioral interval timing. Here, we attempt to decode the lapse of time from neuronal population signals recorded from the frontal cortex of monkeys performing a multiple-interval timing task. We designed a Bayesian algorithm that deciphers temporal information hidden in noisy signals dispersed within the activity of individual neurons recorded from monkeys trained to determine the passage of time before initiating an action. With this decoder, we succeeded in estimating the elapsed time with a precision of approximately 1 s throughout the relevant behavioral period from firing rates of 25 neurons in the pre-supplementary motor area. Further, an extended algorithm makes it possible to determine the total length of the time-interval required to wait in each trial. This enables observers to predict the moment at which the subject will take action from the neuronal activity in the brain. A separate population analysis reveals that the neuronal ensemble represents the lapse of time in a manner scaled relative to the scheduled interval, rather than representing it as the real physical time

Discharge Synchrony during the Transition of Behavioral Goal Representations Encoded by Discharge Rates of Prefrontal Neurons

To investigate the temporal relationship between synchrony in the discharge of neuron pairs and modulation of the discharge rate, we recorded the neuronal activity of the lateral prefrontal cortex of monkeys performing a behavioral task that required them to plan an immediate goal of action to attain a final goal. Information about the final goal was retrieved via visual instruction signals, whereas information about the immediate goal was generated internally. The synchrony of neuron pair discharges was analyzed separately from changes in the firing rate of individual neurons during a preparatory period. We focused on neuron pairs that exhibited a representation of the final goal followed by a representation of the immediate goal at a later stage. We found that changes in synchrony and discharge rates appeared to be complementary at different phases of the behavioral task. Synchrony was maximized during a specific phase in the preparatory period corresponding to a transitional stage when the neuronal activity representing the final goal was replaced with that representing the immediate goal. We hypothesize that the transient increase in discharge synchrony is an indication of a process that facilitates dynamic changes in the prefrontal neural circuits in order to undergo profound state changes

Representational Switching by Dynamical Reorganization of Attractor Structure in a Network Model of the Prefrontal Cortex

The prefrontal cortex (PFC) plays a crucial role in flexible cognitive behavior by representing task relevant information with its working memory. The working memory with sustained neural activity is described as a neural dynamical system composed of multiple attractors, each attractor of which corresponds to an active state of a cell assembly, representing a fragment of information. Recent studies have revealed that the PFC not only represents multiple sets of information but also switches multiple representations and transforms a set of information to another set depending on a given task context. This representational switching between different sets of information is possibly generated endogenously by flexible network dynamics but details of underlying mechanisms are unclear. Here we propose a dynamically reorganizable attractor network model based on certain internal changes in synaptic connectivity, or short-term plasticity. We construct a network model based on a spiking neuron model with dynamical synapses, which can qualitatively reproduce experimentally demonstrated representational switching in the PFC when a monkey was performing a goal-oriented action-planning task. The model holds multiple sets of information that are required for action planning before and after representational switching by reconfiguration of functional cell assemblies. Furthermore, we analyzed population dynamics of this model with a mean field model and show that the changes in cell assemblies' configuration correspond to those in attractor structure that can be viewed as a bifurcation process of the dynamical system. This dynamical reorganization of a neural network could be a key to uncovering the mechanism of flexible information processing in the PFC

Opto-Current-Clamp Actuation of Cortical Neurons Using a Strategically Designed Channelrhodopsin

BACKGROUND: Optogenetic manipulation of a neuronal network enables one to reveal how high-order functions emerge in the central nervous system. One of the Chlamydomonas rhodopsins, channelrhodopsin-1 (ChR1), has several advantages over channelrhodopsin-2 (ChR2) in terms of the photocurrent kinetics. Improved temporal resolution would be expected by the optogenetics using the ChR1 variants with enhanced photocurrents. METHODOLOGY/PRINCIPAL FINDINGS: The photocurrent retardation of ChR1 was overcome by exchanging the sixth helix domain with its counterpart in ChR2 producing Channelrhodopsin-green receiver (ChRGR) with further reform of the molecule. When the ChRGR photocurrent was measured from the expressing HEK293 cells under whole-cell patch clamp, it was preferentially activated by green light and has fast kinetics with minimal desensitization. With its kinetic advantages the use of ChRGR would enable one to inject a current into a neuron by the time course as predicted by the intensity of the shedding light (opto-current clamp). The ChRGR was also expressed in the motor cortical neurons of a mouse using Sindbis pseudovirion vectors. When an oscillatory LED light signal was applied sweeping through frequencies, it robustly evoked action potentials synchronized to the oscillatory light at 5-10 Hz in layer 5 pyramidal cells in the cortical slice. The ChRGR-expressing neurons were also driven in vivo with monitoring local field potentials (LFPs) and the time-frequency energy distribution of the light-evoked response was investigated using wavelet analysis. The oscillatory light enhanced both the in-phase and out-phase responses of LFP at the preferential frequencies of 5-10 Hz. The spread of activity was evidenced by the fact that there were many c-Fos-immunoreactive neurons that were negative for ChRGR in a region of the motor cortex. CONCLUSIONS/SIGNIFICANCE: The opto-current-clamp study suggests that the depolarization of a small number of neurons wakes up the motor cortical network over some critical point to the activated state

Visual Properties of Transgenic Rats Harboring the Channelrhodopsin-2 Gene Regulated by the Thy-1.2 Promoter

Channelrhodopsin-2 (ChR2), one of the archea-type rhodopsins from green algae, is a potentially useful optogenetic tool for restoring vision in patients with photoreceptor degeneration, such as retinitis pigmentosa. If the ChR2 gene is transferred to retinal ganglion cells (RGCs), which send visual information to the brain, the RGCs may be repurposed to act as photoreceptors. In this study, by using a transgenic rat expressing ChR2 specifically in the RGCs under the regulation of a Thy-1.2 promoter, we tested the possibility that direct photoactivation of RGCs could restore effective vision. Although the contrast sensitivities of the optomotor responses of transgenic rats were similar to those observed in the wild-type rats, they were enhanced for visual stimuli of low-spatial frequency after the degeneration of native photoreceptors. This result suggests that the visual signals derived from the ChR2-expressing RGCs were reinterpreted by the brain to form behavior-related vision