Journal of Neurophysiology

JNP Micro Podcasts ”Four Questions”: Jan-Marino (Nino) Ramirez and Nicholas J. Burgraff

Listen to our new micro podcast series where authors, Nicholas J. Burgraff and Jan-Marino (Nino) Ramirez of the Center for Integrative Brain Research, Seattle Children’s Research Institute discuss their recently published research "Inspiratory rhythm generation is stabilized by I_h". 

 

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The Cortical Evoked Potential Corresponds with Deep Brain Stimulation Efficacy in Rats

In this podcast senior author Prof. Warren Grill of Duke University discusses his published manuscript "The cortical evoked potential corresponds with deep brain stimulation efficacy in rats" with Editor in Chief Prof. Nino Ramirez. In this paper the authors characterize a new potential biomarker for deep brain stimulation (DBS), the cortical evoked potential (cEP), and demonstrate that it exhibits a robust correlation with motor behaviors as a function of stimulation frequency. The cEP may thus be a useful clinical biomarker for changes in motor behavior. This work also provides insight into the cortical mechanisms of DBS, suggesting that motor behaviors are strongly affected by the rate of antidromic spike failure during DBS.

 

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How Functional brain states impinge on the fundamental functional organization of the brain in health and disease

In this podcast authors Prof. Albrecht Stroh of the University Medical Center and Leibniz Institute for Resilience Research in Mainz and Dr. Miriam Schwalm of Massachusetts Institute of Technology discuss their recently published manuscript Functional States Shape the Spatiotemporal Representation of Local and Cortex-wide Neural Activity in Mouse Sensory Cortex  with Editor-in-Chief, Prof. Nino Ramirez. The authors work, which was conducted in collaboration with researchers from the University of Washington, compares the cortical representation of two distinct functional states, based on optical and electrophysiological signals, locally recorded in the primary visual and somatosensory area, and wide-field camera imaging of the entire mouse cortex. The authors examined intrinsic and stimulus-evoked neuronal activity under both states and show state-dependent signal propagation modes. As different types of anesthesia as well as different behavioral states show characteristics similar to the two states the authors described, these experiments serve as a model for cortical information processing and explain response variability of neural networks under seemingly constant conditions, which is relevant for a variety of neurophysiological studies.

 

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Covid shows us the importance of smell in cognitive health

In this podcast, Prof. Leslie Kay of The University of Chicago and Associate Editor for the Journal of Neurophysiology discusses her review article “COVID-19 and olfactory dysfunction: a looming wave of dementia?” with Editor in Chief Prof. Nino Ramirez. We find ourselves in the middle of a global “experiment” on the mechanisms of dementia and the relationship between our sense of smell and our ability to think. In many diseases that end in dementia, one of the early signs is olfactory dysfunction, often associated with degeneration in the olfactory bulb. More than 15 million people worldwide experience persistent COVID-19 olfactory changes, possibly caused by olfactory bulb damage. These data suggest a wave of post-COVID dementia in the coming decades, similar to the type of dementia seen in Parkinson’s and Alzheimer’s diseases. We can seize this gruesome opportunity to understand the involvement of the olfactory system in cognitive health. This will require intense study and increased resources to find treatments for smell dysfunction.

 

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The effects of reward on sequential motor behavior

In this podcast, senior author Dr. Joseph Galea of the University of Birmingham discusses his recently published manuscript "The dissociable effects of reward on sequential motor behavior" with Editor-in-Chief, Prof. Nino Ramirez. Joseph M. Galea, et al.'s research provides a mechanistic framework for how reward influences motor behavior. Specifically, the authors show that instantaneous improvements in speed and accuracy are driven by reward presented in the form of money, while knowledge of performance through performance feedback leads to training-based improvements. Importantly, combining both maximized performance gains and led to improvements in movement quality through fusion, which describes an optimization process during which sequential movements blend into a single action. Take a listen today! 

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Self-Organization of Spinal Monosynaptic and Interneuronal Circuitry

In this podcast coauthors Dr. Jonas M.D. Enander of Lund University and Dr. Gerald E. Loeb of the University of Southern California discuss their companion papers titled “A Model for Self-Organization of Sensorimotor Function: The Spinal Monosynaptic Loop" and "Spinal Interneuronal Integration” with Editor in Chief Prof. Nino Ramirez. In the first paper the authors present a model of a simple but biologically realistic musculoskeletal system with spindle primary afferents that become selectively connected to homonymous beta motoneurons as a result of Hebbian adaptation. The second paper models a later stage of spinal cord development in which populations of excitatory and inhibitory interneurons similarly develop patterned connectivity involving a complete set of somatosensory afferents, motoneurons and each other. Without any a priori defined connectivity or organization, Hebbian learning driven by spontaneous, fetal-like motor activity results in the emergence of well-functioning spinal circuits whose connectivity patterns resemble those observed in the adult mammalian spinal cord. The authors suggest that genetic transcriptomes that appear during development may specify phases and rules for adaptive development rather than muscle-specific wiring patterns. The emergent behavior of their model system has important implications for the evolution of new species and potential applications for bio-inspired robots. 

 

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Sensitivity to change in heartbeats as interoceptive ability

What is the nature of autonomic signals and how do they shape introception? This study presents a new method for evaluating cardiac interoceptive ability, measuring sensitivity to naturalistic changes in the number of heartbeats over time periods. The results of this research show participants have an overall tendency towards sensing fewer heartbeats during higher heart rates. This likely reflects the influence of changing heartbeat strength on cardiac interoception at rest, which should be taken into account when evaluating cardiac interoceptive ability and its relationship to anxiety and psychosomatic conditions. Take a listen to this podcast as Dr. Sarah Garfinkel of the University College London discusses the recently published research “Sensitivity to changes in rate of heartbeats as a measure of interoceptive ability” with Editor-in-Chief Professor Nino Ramirez.

 

Dennis E. O. Larsson, Giulia Esposito, Hugo D. Critchley, Zoltan Dienes, and Sarah N. Garfinkel

 

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Oscillatory entrainment mechanisms and anticipatory predictive processes in children with autism spectrum disorder

In this podcast the authors Dr. Shlomit Beker and Dr. Sophie Molholm of Albert Einstein College of Medicine discuss their recently published manuscript titled “Oscillatory entrainment mechanisms and anticipatory predictive processes in Children with Autism Spectrum Disorder (ASD)” with Editor-in-Chief Prof. Jan-Marino (Nino) Ramirez. In their paper they, along with co-author John Foxe, used EEG and behavior to index predictive processes in children with ASD.  A condition in which an auditory target was cued by a rhythmically predictable sequence of visual stimuli was compared to a condition in which the visual cues were absent. Neurophysiological measures of predictive processing, namely preparatory activity and neural entrainment were impaired in the ASD group, whereas behavioral measures of predictive processing were intact.  When sensory events are presented in a predictable temporal pattern, performance and neuronal responses in ASD may be governed more by the occurrence of the events themselves and less by their anticipated timing.  Listen today!

Check out the article here: https://doi.org/10.1152/jn.00329.2021 

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Forms of explanation and understanding for neuroscience and artificial intelligence

In this podcast author Dr. Jessica Thompson of the University of Oxford discusses her recently published manuscript titled "Forms of explanation and understanding for neuroscience and artificial intelligence" with Editor-in-Chief  Prof. Jan-Marino (Nino) Ramirez and Associate Editor Dr. John W. Krakauer.  Much of the controversy evoked by the use of deep neural networks as models of biological neural systems amount to debates over what constitutes scientific progress in neuroscience. In order to discuss what constitutes scientific progress, one must have a goal in mind (progress towards what?). One such long term goal is to produce scientific explanations of intelligent capacities (e.g., object recognition, relational reasoning). I argue that the most pressing philosophical questions at the intersection of neuroscience and artificial intelligence are ultimately concerned with defining the phenomena to be explained and with what constitute valid explanations of such phenomena. I propose that a foundation in the philosophy of scientific explanation and understanding can scaffold future discussions about how an integrated science of intelligence might progress. Towards this vision, I review relevant theories of scientific explanation and discuss strategies for unifying the scientific goals of neuroscience and AI.

 

https://doi.org/10.1152/jn.00195.2021

Temporal Differences between Load and Movement Signal Integration in the Sensorimotor Network of an Insect Leg

Listen as coauthors Dr. Corinna Gebehart and Prof. Ansgar Büschges of the University of Cologne talk about their recently published manuscript "Temporal Differences between Load and Movement Signal Integration in the Sensorimotor Network of an Insect Leg" with Editor-in-Chief Prof. Jan-Marino (Nino) Ramirez. In this podcast the authors discuss  temporal differences in the processing of two distinct sensory modalities generated by the sensorimotor network and affecting motor output. The authors found that the reported temporal differences in sensory processing and signal integration improve our understanding of sensory network computation and function in motor control.

 

Corinna Gebehart, Ansgar Büschges

https://doi.org/10.1152/jn.00399.2021