Flexible resonance in prefrontal networks with strong feedback inhibition

[EN] Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation; and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells; we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering.This material is based upon research supported by the U. S. Army Research Office under award number ARO W911NF-12-R-0012-02 to N. K., the U. S. Office of Naval Research under award number ONR MURI N00014-16-1-2832 to M. H., and the National Science Foundation under award number NSF DMS-1042134 (Cognitive Rhythms Collaborative: A Discovery Network) to N. K. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Sherfey, JS.; Ardid-Ramírez, JS.; Hass, J.; Hasselmo, ME.; Kopell, NJ. (2018). Flexible resonance in prefrontal networks with strong feedback inhibition. 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Signal transduction, receptors, mediators and genes: younger than ever - the 13th meeting of the Signal Transduction Society focused on aging and immunology

The 13th meeting of the Signal Transduction Society was held in Weimar, from October 28 to 30, 2009. Special focus of the 2009 conference was "Aging and Senescence", which was co-organized by the SFB 728 "Environmentally-Induced Aging Processes" of the University of Düsseldorf and the study group 'Signal Transduction' of the German Society for Cell Biology (DGZ). In addition, several other areas of signal transduction research were covered and supported by different consortia associated with the Signal Transduction Society including the long-term associated study groups of the German Society for Immunology and the Society for Biochemistry and Molecular Biology, and for instance the SFB/Transregio 52 "Transcriptional Programming of Individual T Cell Subsets" located in Würzburg, Mainz and Berlin. The different research areas that were introduced by outstanding keynote speakers attracted more than 250 scientists, showing the timeliness and relevance of the interdisciplinary concept and exchange of knowledge during the three days of the scientific program. This report gives an overview of the presentations of the conference

Cross-Modal Distortion of Time Perception: Demerging the Effects of Observed and Performed Motion

Temporal information is often contained in multi-sensory stimuli, but it is currently unknown how the brain combines e.g. visual and auditory cues into a coherent percept of time. The existing studies of cross-modal time perception mainly support the “modality appropriateness hypothesis”, i.e. the domination of auditory temporal cues over visual ones because of the higher precision of audition for time perception. However, these studies suffer from methodical problems and conflicting results. We introduce a novel experimental paradigm to examine cross-modal time perception by combining an auditory time perception task with a visually guided motor task, requiring participants to follow an elliptic movement on a screen with a robotic manipulandum. We find that subjective duration is distorted according to the speed of visually observed movement: The faster the visual motion, the longer the perceived duration. In contrast, the actual execution of the arm movement does not contribute to this effect, but impairs discrimination performance by dual-task interference. We also show that additional training of the motor task attenuates the interference, but does not affect the distortion of subjective duration. The study demonstrates direct influence of visual motion on auditory temporal representations, which is independent of attentional modulation. At the same time, it provides causal support for the notion that time perception and continuous motor timing rely on separate mechanisms, a proposal that was formerly supported by correlational evidence only. The results constitute a counterexample to the modality appropriateness hypothesis and are best explained by Bayesian integration of modality-specific temporal information into a centralized “temporal hub”

Technology transfer model for Austrian higher education institutions

The aim of this paper is to present the findings of a PhD research (Heinzl 2007, Unpublished PhD Thesis) conducted on the Universities of Applied Sciences in Austria. Four of the models that emerge from this research are: Generic Technology Transfer Model (Sect. 5.1); Idiosyncrasies Model for the Austrian Universities of Applied Sciences (Sect. 5.2); Idiosyncrasies-Technology Transfer Effects Model (Sect. 5.3); Idiosyncrasies-Technology Transfer Cumulated Effects Model (Sect. 5.3). The primary and secondary research methods employed for this study are: literature survey, focus groups, participant observation, and interviews. The findings of the research contribute to a conceptual design of a technology transfer system which aims to enhance the higher education institutions' technology transfer performance. © 2012 Springer Science+Business Media, LLC

Constraints on persistent activity in a biologically detailed network model of the prefrontal cortex with heterogeneities

[EN] Persistent activity, the maintenance of neural activation over short periods of time in cortical networks, is widely thought to underlie the cognitive function of working memory. A large body of modeling studies has reproduced this kind of activity using cell assemblies with strengthened synaptic connections. However, almost all of these studies have considered persistent activity within networks with homogeneous neurons and synapses, making it difficult to judge the validity of such model results for cortical dynamics, which is based on highly heterogeneous neurons. Here, we consider persistent activity in a detailed, strongly data-driven network model of the prefrontal cortex with heterogeneous neuron and synapse parameters. Surprisingly, persistent activity could not be reproduced in this model without incorporating further constraints. We identified three factors that prevent successful persistent activity: heterogeneity in the cell parameters of interneurons, heterogeneity in the parameters of short-term synaptic plasticity and heterogeneity in the synaptic weights. We also discovered a general dynamic mechanism that prevents persistent activity in the presence of heterogeneities, namely a gradual drop-out of cell assembly neurons out of a bistable regime as input variability increases. Based on this mechanism, we found that persistent activity is recovered if heterogeneity is compensated, e.g., by a homeostatic plasticity mechanism. Cell assemblies shaped in this way may be potentially targeted by distinct inputs or become more responsive to specific tuning or spectral properties. Finally, we show that persistent activity in the model is robust against external noise, but the compensation of heterogeneities may prevent the dynamic generation of intrinsic in vivo-like irregular activity. These results may help informing the ongoing debate about the neural basis of working memory.We thank Michelle McCarthy for valuable discussions during this research. This work was supported by the Army Research Office [Award no. ARO W911NF-12-R-0012-02] , Heidelberg Academy of Sciences and Humanities [6. Teilprogramm WIN-Programm] , Generalitat Valenciana Gen-T Program [Ref. CIDEGENT/2019/043] and Grant PID2020-120037GA-I00 funded by MCIN/AEI/10.13039/501100011033.Hass, J.; Ardid, S.; Sherfey, J.; Kopell, N. (2022). Constraints on persistent activity in a biologically detailed network model of the prefrontal cortex with heterogeneities. Progress in Neurobiology. 215:1-18. https://doi.org/10.1016/j.pneurobio.2022.10228711821

An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data

For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx) model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like') input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available

Family-centered music therapy-Empowering premature infants and their primary caregivers through music: Results of a pilot study.

BackgroundIn Neonatal Intensive Care Units (NICUs) premature infants are exposed to various acoustic, environmental and emotional stressors which have a negative impact on their development and the mental health of their parents. Family-centred music therapy bears the potential to positively influence these stressors. The few existing studies indicate that interactive live-improvised music therapy interventions both reduce parental stress factors and support preterm infants' development.MethodsThe present randomized controlled longitudinal study (RCT) with very low and extremely low birth weight infants (born ResultsCompared to the control group, infants in the treatment group showed a 11.1 days shortening of caffeine therapy, 12.1 days shortening of nasogastric/ orogastric tube feed and 15.5 days shortening of hospitalization, on average. While these differences were not statistically significant, a factor-analytical compound measure of all three therapy durations was. From pre-to-post-intervention, parents showed a significant reduction in stress factors. However, there were no differences between control and treatment group. A regression analysis showed links between parental stress factors and physiological development of the infants.ConclusionThis pilot study suggests that a live-improvised interactive music therapy intervention for extremely and very preterm infants and their parents may have a beneficial effect on the therapy duration needed for premature infants before discharge from hospital is possible. The study identified components of the original physiological variables of the infants as appropriate endpoints and suggested a slight change in study design to capture possible effects of music therapy on infants' development as well. Further studies should assess both short-term and long-term effects on premature infants as well as on maternal and paternal health outcomes, to determine whether a family-centered music therapy, actually experienced as an added value to developmental care, should be part of routine care at the NICU

The human mirror neuron system : a common neural basis for social cognition?

According to the theory of embodied simulation, mirror neurons (MN) in our brain's motor system are the neuronal basis of all social-cognitive processes. The assumption of such a mirroring process in humans could be supported by results showing that within one person the same region is involved in different social cognition tasks. We conducted an fMRI-study with 75 healthy participants who completed three tasks: imitation, empathy, and theory of mind. We analyzed the data using group conjunction analyses and individual shared voxel counts. Across tasks, across and within participants, we find common activation in inferior frontal gyrus, inferior parietal cortex, fusiform gyrus, posterior superior temporal sulcus, and amygdala. Our results provide evidence for a shared neural basis for different social-cognitive processes, indicating that interpersonal understanding might occur by embodied simulation.publishe