Tactile object categories can be decoded from the parietal and lateral-occipital cortices

Resting-State Network Plasticity Following Category Learning Depends on Sensory Modality

Learning new categories is fundamental to cognition, occurring in daily life through various sensory modalities. However, it is not well known how acquiring new categories can modulate the brain networks. Resting-state functional connectivity is an effective method for detecting short-term brain alterations induced by various modality-based learning experiences. Using fMRI, our study investigated the intricate link between novel category learning and brain network reorganization. Eighty-four adults participated in an object categorization experiment utilizing visual (n = 41, with 20 females and a mean age of 23.91 ± 3.11 years) or tactile (n = 43, with 21 females and a mean age of 24.57 ± 2.58 years) modalities. Resting-state networks (RSNs) were identified using independent component analysis across the group of participants, and their correlation with individual differences in object category learning across modalities was examined using dual regression. Our results reveal an increased functional connectivity of the frontoparietal network with the left superior frontal gyrus in visual category learning task and with the right superior occipital gyrus and the left middle temporal gyrus after tactile category learning. Moreover, the somatomotor network demonstrated an increased functional connectivity with the left parahippocampus exclusively after tactile category learning. These findings illuminate the neural mechanisms of novel category learning, emphasizing distinct brain networks' roles in diverse modalities. The dynamic nature of RSNs emphasizes the ongoing adaptability of the brain, which is essential for efficient novel object category learning. This research provides valuable insights into the dynamic interplay between sensory learning, brain plasticity, and network reorganization, advancing our understanding of cognitive processes across different modalities.

Neuronal tuning and population representations of shape and category in human visual cortex

Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed large-scale recordings of spiking activity in human Lateral Occipital Complex in response to stimuli in which the shape dimension was dissociated from the category dimension. Consistent with studies in nonhuman primates, the neuronal representations were primarily shape-based, although we also observed category-like encoding for images of animals. Surprisingly, linear decoders could reliably classify stimulus category even in data sets that were entirely shape-based. In addition, many recording sites showed an interaction between shape and category tuning. These results represent a detailed study on shape and category coding at the neuronal level in the human ventral visual stream, furnishing essential evidence that reconciles human imaging and macaque single-cell studies.

Visual and Tactile Sensory Systems Share Common Features in Object Recognition

Although we use our visual and tactile sensory systems interchangeably for object recognition on a daily basis, little is known about the mechanism underlying this ability. This study examined how 3D shape features of objects form two congruent and interchangeable visual and tactile perceptual spaces in healthy male and female participants. Since active exploration plays an important role in shape processing, a virtual reality environment was used to visually explore 3D objects called digital embryos without using the tactile sense. In addition, during the tactile procedure, blindfolded participants actively palpated a 3D-printed version of the same objects with both hands. We first demonstrated that the visual and tactile perceptual spaces were highly similar. We then extracted a series of 3D shape features to investigate how visual and tactile exploration can lead to the correct identification of the relationships between objects. The results indicate that both modalities share the same shape features to form highly similar veridical spaces. This finding suggests that visual and tactile systems might apply similar cognitive processes to sensory inputs that enable humans to rely merely on one modality in the absence of another to recognize surrounding objects.

Grasping and Manipulation: Neural Bases and Anatomical Circuitry in Humans

Neurophysiological and neuroimaging evidence suggests a significant contribution of several brain areas, including subdivisions of the parietal and the premotor cortex, during the processing of different components of hand and arm movements. Many investigations improved our knowledge about the neural processes underlying the execution of reaching and grasping actions, while few studies have directly investigated object manipulation. Most studies on the latter topic concern the use of tools to achieve specific goals. Yet, there are very few studies on pure manipulation performed in order to explore and recognize objects, as well as on manipulation performed with a high level of manual dexterity. Another dimension that is quite neglected by the available studies on grasping and manipulation is, on the one hand, the contribution of the subcortical nodes, first of all the basal ganglia and cerebellum, to these functions, and, on the other hand, recurrent connections of these structures with cortical areas. In the first part, we have reviewed the parieto-premotor and subcortical circuits underlying reaching and grasping in humans, with a focus on functional neuroimaging data. Then, we have described the main structures recruited during object manipulation. We have also reported the contribution of recent structural connectivity techniques whereby the cortico-cortical and cortico-subcortical connections of grasping-related and manipulation-related areas in the human brain can be determined. Based on our review, we have concluded that studies on cortical and subcortical circuits involved in grasping and manipulation might be promising to provide new insights about motor learning and brain plasticity in patients with motor disorders.

Cortical Regions Encoding Hardness Perception Modulated by Visual Information Identified by Functional Magnetic Resonance Imaging With Multivoxel Pattern Analysis

Recent studies have revealed that hardness perception is determined by visual information along with the haptic input. This study investigated the cortical regions involved in hardness perception modulated by visual information using functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA). Twenty-two healthy participants were enrolled. They were required to place their left and right hands at the front and back, respectively, of a mirror attached to a platform placed above them while lying in a magnetic resonance scanner. In conditions SFT, MED, and HRD, one of three polyurethane foam pads of varying hardness (soft, medium, and hard, respectively) was presented to the left hand in a given trial, while only the medium pad was presented to the right hand in all trials. MED was defined as the control condition, because the visual and haptic information was congruent. During the scan, the participants were required to push the pad with the both hands while observing the reflection of the left hand and estimate the hardness of the pad perceived by the right (hidden) hand based on magnitude estimation. Behavioral results showed that the perceived hardness was significantly biased toward softer or harder in >73% of the trials in conditions SFT and HRD; we designated these trials as visually modulated (SFTvm and HRDvm, respectively). The accuracy map was calculated individually for each of the pair-wise comparisons of (SFTvm vs. MED), (HRDvm vs. MED), and (SFTvm vs. HRDvm) by a searchlight MVPA, and the cortical regions encoding the perceived hardness with visual modulation were identified by conjunction of the three accuracy maps in group analysis. The cluster was observed in the right sensory motor cortex, left anterior intraparietal sulcus (aIPS), bilateral parietal operculum (PO), and occipito-temporal cortex (OTC). Together with previous findings on such cortical regions, we conclude that the visual information of finger movements processed in the OTC may be integrated with haptic input in the left aIPS, and the subjective hardness perceived by the right hand with visual modulation may be processed in the cortical network between the left PO and aIPS.

Active Haptic Perception in Robots: A Review

In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today's new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data.

State-dependent encoding of sound and behavioral meaning in a tertiary region of the ferret auditory cortex

In higher sensory cortices, there is a gradual transformation from sensation to perception and action. In the auditory system, this transformation is revealed by responses in the rostral ventral posterior auditory field (VPr), a tertiary area in the ferret auditory cortex, which shows long-term learning in trained compared to naïve animals, arising from selectively enhanced responses to behaviorally relevant target stimuli. This enhanced representation is further amplified during active performance of spectral or temporal auditory discrimination tasks. VPr also shows sustained short-term memory activity after target stimulus offset, correlated with task response timing and action. These task-related changes in auditory filter properties enable VPr neurons to quickly and nimbly switch between different responses to the same acoustic stimuli, reflecting either spectrotemporal properties, timing, or behavioral meaning of the sound. Furthermore, they demonstrate an interaction between the dynamics of short-term attention and long-term learning, as incoming sound is selectively attended, recognized, and translated into action.