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1. Subcortical responses to music and speech are alike while cortical responses diverge

   https://doi.org/10.1038/s41598-023-50438-0  

   Shan, Tong; Cappelloni, Madeline S; Maddox, Ross K (January 2024, Scientific Reports)

   Music and speech are encountered daily and are unique to human beings. Both are transformed by the auditory pathway from an initial acoustical encoding to higher level cognition. Studies of cortex have revealed distinct brain responses to music and speech, but differences may emerge in the cortex or may be inherited from different subcortical encoding. In the first part of this study, we derived the human auditory brainstem response (ABR), a measure of subcortical encoding, to recorded music and speech using two analysis methods. The first method, described previously and acoustically based, yielded very different ABRs between the two sound classes. The second method, however, developed here and based on a physiological model of the auditory periphery, gave highly correlated responses to music and speech. We determined the superiority of the second method through several metrics, suggesting there is no appreciable impact of stimulus class (i.e., music vs speech) on the way stimulus acoustics are encoded subcortically. In this study’s second part, we considered the cortex. Our new analysis method resulted in cortical music and speech responses becoming more similar but with remaining differences. The subcortical and cortical results taken together suggest that there is evidence for stimulus-class dependent processing of music and speech at the cortical but not subcortical level. 

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2. Thermomagnetic responses of semimetals

   https://doi.org/10.1063/5.0192824  

   Akhanda, Md_Sabbir; Schlaak, Katherine_A; Scott, Eleanor_F; Afroj_Taj, Md_Nasim; Watzman, Sarah_J; Zebarjadi, Mona (June 2024, Journal of Applied Physics)

   Solid-state thermomagnetic modules operating based on the Nernst–Ettingshausen effects are an alternative to conventional solid-state thermoelectric modules. These modules are appropriate for low-temperature applications where the thermoelectric modules are not efficient. Here, we briefly discuss the application, performance, similarities, and differences of thermoelectric and thermomagnetic materials and modules. We review thermomagnetic module design, Nernst coefficient measurement techniques, and theoretical advances, emphasizing the Nernst effect and factors influencing its response in semimetals such as carrier compensation, Fermi surface, mobility, phonon drag, and Berry curvature. The main objective is to summarize the materials design criteria to achieve high thermomagnetic performance to accelerate thermomagnetic materials discovery. 

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3. Cytonuclear responses to genome doubling

   https://doi.org/10.3732/ajb.1700293  

   Sharbrough, Joel; Conover, Justin L.; Tate, Jennifer A.; Wendel, Jonathan F.; Sloan, Daniel B. (September 2017, American Journal of Botany)
4. T cell immune responses deciphered

   https://doi.org/10.1126/science.abq1679  

   Nourmohammad, Armita (May 2022, Science)

   An immune response involves a coordinated orchestra of antigen-recognizing cells ( e.g. , T cells) and signaling molecules to mount a specific response against a pathogen. Although systems immunology offers a growing list of molecular interactions that are involved in antigen-specific immune responses, an understanding of how a response is mediated by different antigen characteristics is still lacking. On page 880 of this issue, Achar et al. ( 1 ) address this question by using a robotic platform to survey a broad range of functional T cell responses to different antigen stimulations. Using machine learning, they construct a simplified map that separates six different stereotypical classes of antigen-dependent immune responses. Understanding this antigen-encoding could help guide immunotherapy, including engineering chimeric antigen receptor (CAR)–T cells and identifying vaccine antigens. 

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5. Encoding manifolds constructed from grating responses organize responses to natural scenes in cortical visual areas

   https://doi.org/10.1101/2024.10.24.620089  

   Dyballa, Luciano; Field, Greg D; Stryker, Michael P; Zucker, Steven W (October 2024, bioRxiv.org)

   We have created encoding manifolds to reveal the overall responses of a brain area to a variety of stimuli. Encoding manifolds organize response properties globally: each point on an encoding manifold is a neuron, and nearby neurons respond similarly to the stimulus ensemble in time. We previously found, using a large stimulus ensemble including optic flows, that encoding manifolds for the retina were highly clustered, with each cluster corresponding to a different ganglion cell type. In contrast, the topology of the V1 manifold was continuous. Now, using responses of individual neurons from the Allen Institute Visual Coding-Neuropixels dataset in the mouse, we infer encoding manifolds for V1 and for five higher cortical visual areas (VISam, VISal, VISpm, VISlm, and VISrl). We show here that the encoding manifold topology computed only from responses to various grating stimuli is also continuous, not only for V1 but also for the higher visual areas, with smooth coordinates spanning it that include, among others, orientation selectivity and firing-rate magnitude. Surprisingly, the encoding manifold for gratings also provides information about natural scene responses. To investigate whether neurons respond more strongly to gratings or natural scenes, we plot the log ratio of natural scene responses to grating responses (mean firing rates) on the encoding manifold. This reveals a global coordinate axis organizing neurons' preferences between these two stimuli. This coordinate is orthogonal (i.e., uncorrelated) to that organizing firing rate magnitudes in VISp. Analyzing layer responses, a preference for gratings is concentrated in layer 6, whereas preference for natural scenes tends to be higher in layers 2/3 and 4. We also find that preference for natural scenes dominates the responses of neurons that prefer low (0.02 cpd) and high (0.32 cpd) spatial frequencies, rather than intermediate ones (0.04 to 0.16 cpd). Conclusion: while gratings seem limited and natural scenes unconstrained, machine learning algorithms can reveal subtle relationships between them beyond linear techniques. 

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