The Perirhinal Cortex Engages in Area and Layer-Specific Encoding of Item Dimensions

The perirhinal cortex (PRC), subdivided into areas 35 and 36, belongs to the parahippocampal regions that provide polysensory input to the hippocampus. Efferent and afferent connections along its rostro-caudal axis, and of areas 35 and 36, are extremely diverse. Correspondingly functional tasks in which the PRC participates are manifold. The PRC engages, for example, in sensory information processing, object recognition, and attentional processes. It was previously reported that layer II of the caudal area 35 may be critically involved in the encoding of large-scale objects. In the present study we aimed to disambiguate the roles of the different PRC layers, along with areas 35 and 36, and the rostro-caudal compartments of the PRC, in processing information about objects of different dimensions. Here, we compared effects on information encoding triggered by learning about subtle and discretely visible (microscale) object information and overt, highly visible landmark (macroscale) information. To this end, nuclear expression of the immediate early gene Arc was evaluated using fluorescence in situ hybridization. Increased nuclear Arc expression occurred in layers III and V-VI of the middle and caudal parts of area 35 in response to both novel microscale and macroscale object exposure. By contrast, a significant increase in Arc expression occurred in area 36 only in response to microscale objects. These results indicate that area 36 is specifically involved in the encoding of small and less prominently visible items. In contrast, area 35 engages globally (layer III to VI) in the encoding of object information independent of item dimensions.

Spatiotemporal Characteristics of Event-Related Potentials Triggered by Unexpected Events during Simulated Driving and Influence of Vigilance

We investigated the spatiotemporal characteristics of brain activity due to sudden events during monotonous driving and how it changes with vigilance level. Two types of sudden events, emergency stop and car drifting, were presented using driving simulator, and event-related potentials (ERPs) were measured. From the ERPs of both types of events, an early component representing sensory information processing and a late component were observed. The early component was expected to represent sensory information processing, which corresponded to visual and somatosensory/vestibular information processing for the sudden stop and lane departure tasks, respectively. The late components showed spatiotemporal characteristics of the well-known P300 component for both types of events. Common characteristic brain activities occurred in response to sudden events, regardless of the type. The modulation of brain activity due to the vigilance level also shared common characteristics between the two types. We expect that our results will contribute to the development of an effective means to assist drivers’ reactions to ambulatory situations.

Food Texture Acceptance, Sensory Sensitivity, and Food Neophobia in Children and Their Parents

This study aims to explore whether children’s food texture preferences are associated with different levels of sensory sensitivity and food neophobia, as well as with other variables, such as parental texture preferences. An online questionnaire was completed by 70 children aged 6–13 years old, alongside one of their parents. Generic texture preferences of children and parents were investigated with the Child Food Texture Preference Questionnaire (CFTPQ). Parents provided background information about their children by completing the Food Neophobia Scale (FNS), the Short Sensory Profile (SSP) and a Food Frequency Questionnaire (FFQ). The results showed that children who differed in their texture-liker status also differed in their levels of food neophobia and sensory information processing: children who preferred softer and non-particulate versions of foods were found to be more neophobic and sensory sensitive across all sensory domains. No relationship was found between parental and children’s texture preferences.

Whole animal modelling reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming in frog tadpoles

Animal behaviour is based on interaction between nervous, musculoskeletal and environmental systems. How does an animal process sensory stimuli, use it to decide whether and how to respond, and initiate the locomotor behaviour? We build the whole body computer models of a simple vertebrate with a complete chain of neural circuits and body units for sensory information processing, decision-making, generation of spiking activities, muscle innervation, body flexion, body-water interaction, and movement. Our Central Nervous System (CNS) model generates biologically-realistic spiking and reveals that sensory memory populations on two hindbrain sides compete for swimming initiation and first body flexion. Biomechanical 3-dimensional "Virtual Tadpole" (VT) model is constructed to evaluate if motor outputs of CNS model can produce swimming-like movements in a volume of "water". We find that whole animal modelling generates reliable and realistic swimming. The combination of CNS and VT models opens a new perspective for experiments with immobilised tadpoles.

Study of sensory information processing depending on visual stimulus complexity based on multichannel EEG signals

Introduction: Analysis of electrical activity in the cortical neural network during the processing of visual information is one ofthe most interesting issues in modern neuroscience. The particular attention of the researchers is attracted by the study of neuralactivity during complex visual stimuli processing. Purpose: Studying the process of sensory information processing in the corticalneural network based on recorded electrical activity signals (EEG). Results: We have studied neural activity during visual informationprocessing based on the stimulus-related change in the spectral EEG energy in the 15–30 Hz frequency band. Using the developedapproach, we analyzed the influence of the visual stimulus complexity on the features of spatio-temporal neural activity. It has beenfound that at low complexity the spectral amplitude of the EEG in the range of 15–30 Hz increases mainly in the parietal zone. Withincreasing complexity, the spectral amplitude of the EEG increases simultaneously in different parts of the cortex, mainly in the frontalregion. Practical relevance: The identified features of neural dynamics can be used in the development of passive brain-computerinterfaces to monitor a person’s cognitive state and evaluate the cognitive load in real time.

Generalization of the resource-rationality principle to neural control of goal-directed movements

We review evidence that the resource-rationality principle generalizes to human movement control. Optimization of the use of limited neurocomputational resources is described by the inclusion of the “neurocomputational cost” of sensory information processing and decision making in the optimality criterion of movement control. A resulting tendency to decrease this cost can account for various phenomena observed during goal-directed movements.

Coherent resonance in the distributed cortical network during sensory information processing

Neuronal brain network is a distributed computing system, whose architecture is dynamically adjusted to provide optimal performance of sensory processing. A small amount of visual information needed effortlessly be processed, activates neural activity in occipital and parietal areas. Conversely, a visual task which requires sustained attention to process a large amount of sensory information, involves a set of long-distance connections between parietal and frontal areas coordinating the activity of these distant brain regions. We demonstrate that while neural interactions result in coherence, the strongest connection is achieved through coherence resonance induced by adjusting intrinsic brain noise.