Intracortical human recordings reveal intensity coding for the pain of others in the insula

Based on neuroimaging data, the insula is considered important for people to empathize with the pain of others, whether that pain is perceived through facial expressions or the sight of limbs in painful situations. Here we present the first report of intracortical electroencephalographic (iEEG) recordings from the insulae collected while 7 presurgical epilepsy patients rated the intensity of a woman's painful experiences viewed in movies. In two separate conditions, pain was deduced from seeing facial expressions or a hand being slapped by a belt. We found that broadband activity in the 20-190 Hz range correlated with the trial-by-trial perceived intensity in the insula for both types of stimuli. Using microwires at the tip of a selection of the electrodes, we additionally isolated 8 insular neurons with spiking that correlated with perceived intensity. Within the insula, we found a patchwork of locations with differing selectivities within our stimulus set, some representing intensity only for facial expressions, others only for the hand being hit, and others for both. That we found some locations with intensity coding only for faces, and others only for hand across simultaneously recorded locations suggests that insular activity while witnessing the pain of others cannot be entirely reduced to a univariate salience representation. Psychophysics and the temporal properties of our signals indicate that the timing of responses encoding intensity for the sight of the hand being hit are best explained by kinematic information; the timing of those encoding intensity for the facial expressions are best explained by shape information in the face. In particular, the furrowing of the eyebrows and the narrowing of the eyes of the protagonist in the movies suffice to predict both the rating of and the timing of the neuronal response to the facial expressions. Comparing the broadband activity in the iEEG signal with spiking activity and an fMRI experiment with similar stimuli revealed a consistent spatial organization for the representation of intensity from our hand stimuli, with stronger intensity representation more anteriorly and around neurons with intensity coding. In contrast, for the facial expressions, we found that the activity at the three levels of measurement do not coincide, suggesting a more disorganized representation. Together, our intracortical recordings indicate that the insula encodes, in a partially intermixed layout, both static and dynamic cues from different body parts that reflect the intensity of pain experienced by others.

Gradients in the biophysical properties of neonatal auditory neurons align with synaptic contact position and the intensity coding map of inner hair cells

Sound intensity is encoded by auditory neuron subgroups that differ in thresholds and spontaneous rates. Whether variations in neuronal biophysics contributes to this functional diversity is unknown. Because intensity thresholds correlate with synaptic position on sensory hair cells, we combined patch clamping with fiber labeling in semi-intact cochlear preparations in neonatal rats from both sexes. The biophysical properties of auditory neurons vary in a striking spatial gradient with synaptic position. Neurons with high thresholds to injected currents contact hair cells at synaptic positions where neurons with high thresholds to sound-intensity are found in vivo. Alignment between in vitro and in vivo thresholds suggests that biophysical variability contributes to intensity coding. Biophysical gradients were evident at all ages examined, indicating that cell diversity emerges in early post-natal development and persists even after continued maturation. This stability enabled a remarkably successful model for predicting synaptic position based solely on biophysical properties.

Age-related changes in sound onset and offset intensity coding in auditory cortical fields A1 and CL of rhesus macaques

Inhibition plays a key role in shaping sensory processing in the central auditory system and has been implicated in sculpting receptive field properties such as sound intensity coding and also in shaping temporal patterns of neuronal firing such as onset- or offset-evoked responses. There is substantial evidence supporting a decrease in inhibition throughout the ascending auditory pathway in geriatric animals. We therefore examined intensity coding of onset (ON) and offset (OFF) responses in auditory cortex of aged and young monkeys. A large proportion of cells in the primary auditory cortex (A1) and the caudolateral field (CL) displayed nonmonotonic rate-level functions for OFF responses in addition to nonmonotonic coding of ON responses. Aging differentially affected ON and OFF responses; the magnitude of effects was generally greater for ON responses. In addition to higher firing rates, neurons in old monkeys exhibited a significant increase in the proportion of monotonic rate-level functions and had higher best intensities than those in young monkeys. OFF responses in young monkeys displayed a range of intensity coding relationships with ON responses of the same cells, ranging from highly similar to highly dissimilar. Dissimilarity in ON/OFF coding was greater in CL and was reduced with aging, which was largely explained by a preferential decrease in the percentage of cells with nonmonotonic coding of ON and OFF responses. The changes we observed are consistent with previously demonstrated alterations in inhibition in the ascending auditory pathway of primates and could be involved in age-related deficits in the temporal processing of sounds. NEW & NOTEWORTHY Aging has a major impact on intensity coding of neurons in auditory cortex of rhesus macaques. Neural responses to sound onset and offset were affected to different extents, and their rate-level functions became more mutually similar, which could be accounted for by the loss of nonmonotonic intensity coding in geriatric monkeys. These findings were consistent with weakened inhibition in the central auditory system and could contribute to auditory processing deficits in elderly subjects.

MIC_Locator: a novel image-based protein subcellular location multi-label prediction model based on multi-scale monogenic signal representation and intensity encoding strategy

Background Protein subcellular localization plays a crucial role in understanding cell function. Proteins need to be in the right place at the right time, and combine with the corresponding molecules to fulfill their functions. Furthermore, prediction of protein subcellular location not only should be a guiding role in drug design and development due to potential molecular targets but also be an essential role in genome annotation. Taking the current status of image-based protein subcellular localization as an example, there are three common drawbacks, i.e., obsolete datasets without updating label information, stereotypical feature descriptor on spatial domain or grey level, and single-function prediction algorithm’s limited capacity of handling single-label database. Results In this paper, a novel human protein subcellular localization prediction model MIC_Locator is proposed. Firstly, the latest datasets are collected and collated as our benchmark dataset instead of obsolete data while training prediction model. Secondly, Fourier transformation, Riesz transformation, Log-Gabor filter and intensity coding strategy are employed to obtain frequency feature based on three components of monogenic signal with different frequency scales. Thirdly, a chained prediction model is proposed to handle multi-label instead of single-label datasets. The experiment results showed that the MIC_Locator can achieve 60.56% subset accuracy and outperform the existing majority of prediction models, and the frequency feature and intensity coding strategy can be conducive to improving the classification accuracy. Conclusions Our results demonstrate that the frequency feature is more beneficial for improving the performance of model compared to features extracted from spatial domain, and the MIC_Locator proposed in this paper can speed up validation of protein annotation, knowledge of protein function and proteomics research.