A. D. (Bud) Craig, Jr. (1951–2023)Blomqvist, Anders; Evrard, Henry C.; Dostrovsky, Jonathan O.; Strigo, Irina A.; Jänig, Wilfrid
doi: 10.1038/s41593-023-01463-9pmid: 37749257
Bud Craig, an outstanding neuroscientist, died on 15 July 2023 at age 71. Bud made unique contributions to the fields of pain and interoception, challenging major dogmas and offering powerful explanations for various phenomena including central pain and the subjective awareness of feelings, with great implications for our understanding of consciousness.
Humans can intermittently respond to verbal stimuli when sleepingdoi: 10.1038/s41593-023-01450-0pmid: 37828229
Sleep is typically considered as a state of behavioral disconnection from the outside world. Recordings of brain activity and facial muscle tone during sleep reveal that humans can respond to external stimuli across most sleep stages. These windows of behavioral responsiveness reveal transient episodes of high-cognitive states with electrophysiological signatures suggestive of a conscious state.
A European perspective on structural barriers to women’s career progression in neuroscienceBourke, Ashley M.; Spanò, Teresa; Schuman, Erin M.
doi: 10.1038/s41593-023-01467-5pmid: 37872304
Despite an unprecedented number of women entering neuroscience, and decades-long recruitment and retention efforts, women continue to be disproportionately underrepresented in European academic tenure-track faculty and leadership positions. This Perspective focuses on two major career points where women exhibit diminished representation: the transition from postdoctoral fellow to junior professor and the promotion to more senior (tenured) faculty positions. We discuss below recently implemented country-specific and Europe-wide initiatives supporting equal career progression and propose further concrete steps to be taken to break down the structural barriers that prevent women’s progression up the academic career ladder as European neuroscientists.
A conceptual framework for astrocyte functionMurphy-Royal, Ciaran; Ching, ShiNung; Papouin, Thomas
doi: 10.1038/s41593-023-01448-8pmid: 37857773
The participation of astrocytes in brain computation was hypothesized in 1992, coinciding with the discovery that these cells display a form of intracellular Ca2+ signaling sensitive to neuroactive molecules. This finding fostered conceptual leaps crystalized around the idea that astrocytes, once thought to be passive, participate actively in brain signaling and outputs. A multitude of disparate roles of astrocytes has since emerged, but their meaningful integration has been muddied by the lack of consensus and models of how we conceive the functional position of these cells in brain circuitry. In this Perspective, we propose an intuitive, data-driven and transferable conceptual framework we coin ‘contextual guidance’. It describes astrocytes as ‘contextual gates’ that shape neural circuitry in an adaptive, state-dependent fashion. This paradigm provides fresh perspectives on principles of astrocyte signaling and its relevance to brain function, which could spur new experimental avenues, including in computational space.
Studying the neural representations of uncertaintyWalker, Edgar Y.; Pohl, Stephan; Denison, Rachel N.; Barack, David L.; Lee, Jennifer; Block, Ned; Ma, Wei Ji; Meyniel, Florent
doi: 10.1038/s41593-023-01444-ypmid: 37814025
The study of the brain’s representations of uncertainty is a central topic in neuroscience. Unlike most quantities of which the neural representation is studied, uncertainty is a property of an observer’s beliefs about the world, which poses specific methodological challenges. We analyze how the literature on the neural representations of uncertainty addresses those challenges and distinguish between ‘code-driven’ and ‘correlational’ approaches. Code-driven approaches make assumptions about the neural code for representing world states and the associated uncertainty. By contrast, correlational approaches search for relationships between uncertainty and neural activity without constraints on the neural representation of the world state that this uncertainty accompanies. To compare these two approaches, we apply several criteria for neural representations: sensitivity, specificity, invariance and functionality. Our analysis reveals that the two approaches lead to different but complementary findings, shaping new research questions and guiding future experiments.