Specific Heats of Fe-Ni (fcc) Alloys at High Temperature

Specific heats at constant pressure, C_p, of Fe-Ni (fcc) alloys have been measured a temperatures 300～1000 K. For alloys containing more than 50%Ni, the C_p-T curve shows a sharp λ-type peak at ferromagnetic Curie temperature. For the alloys less in concentration of nickel, however, only a dull peak is observed. The C_p-T curve is analyzed using the values of thermal expansion coefficient and of compressibility measured on the same conditions, separating the magnetic contribution from total specific heats

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

Detecting immunoglobulin G4-related intracranial arteriopathy with magnetic resonance vessel wall imaging: a preliminary experience in two cases

[Background] Detecting immunoglobulin G4 (IgG4)-related intracranial arteriopathy, a rare neurovascular complication of IgG4-related disease, is challenging. While magnetic resonance (MR) vessel wall imaging (VWI) can visualize various neurovascular pathologies, its application to this arteriopathy has not been reported as of this writing. [Case presentation] A 74-year-old male and a 65-year-old female manifested multiple cranial nerve palsy and neck pain, respectively. Both cases exhibited multiorgan masses with markedly elevated serum IgG4 levels and were clinically diagnosed with IgG4-related disease. Three-dimensional T1-weighted black blood VWI with and without contrast agent identified intracranial vascular lesions characterized as nearly-circumferential mural thickening with homogeneous contrast enhancement in the internal carotid and vertebral arteries; some of the lesions had been unrecognized with screening MR angiography due to expansive remodeling. The former patient underwent corticosteroid therapy, and VWI after treatment revealed decreased mural thickening and enhancement. [Conclusion] Further studies to elucidate characteristic findings of VWI might contribute to early detection of this treatable pathology

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

Two-dimensional representation of action and arm-use sequences in the presupplementary and supplementary motor areas

The medial frontal cortex has been thought to be crucially involved in temporal structuring of behavior in monkeys and humans. We examined neuronal activity in the supplementary and presupplementary motor areas of monkeys to investigate how the nervous system deals with the coding of 16 motor sequences resulting from multiple actions involving bilateral use of the arms. We first found in both areas that this behavioral demand resulted in attribute-based representation of individual motor acts, reflecting functional (action) or anatomical (right/left arm) attributes. Actions were frequently represented according to a body-axis-centered reference frame (supination or pronation) regardless of the arm to be used. Moreover, behavioral sequences were primarily represented with respect to the action- or arm-use sequence rather than the sequence of individual movements. We propose that the two-dimensional attribute-based sequence representation provides a robust and efficient means of processing multiple behavioral sequences