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Error correction is central to fault-tolerant quantum computation, but although various schemes have been developed in theory, there are few experimental realizations; a quantum error correction process is now reported for a single system of electron and nuclear spins residing in a diamond crystal. Practical quantum error correction Quantum information processing has the potential to be very powerful, solving problems that classical computing cannot even address. One drawback is its reliance on fragile resources -- quantum superposition and entanglement -- that are easily perturbed. Error correction is therefore central to fault-tolerant quantum computation and although various schemes have been proposed, there are few experimental realizations. Gerald Waldherr et al. successfully demonstrate a quantum error correction process on a system of electron and nuclear spins residing in a diamond crystal. Three nearby nuclear spins form the three entangled quantum bits (qubits) that are necessary for a quantum error correction protocol and the interaction with an electron spin enables readout. This new approach is applicable to other solid-state hybrid quantum spin systems such as those based on dopants in silicon. Error correction is important in classical and quantum computation. Decoherence caused by the inevitable interaction of quantum bits with their environment leads to dephasing or even relaxation. Correction of the concomitant errors is therefore a fundamental requirement for scalable quantum computation.sup.1,2,3,4,5,6,7. Although algorithms for error correction have been known for some time, experimental realizations are scarce.sup.2,3,4,5,6,7. Here we show quantum error correction in a heterogeneous, solid-state spin system.sup.8,9,10,11,12,13,14,15,16,17,18,19,20,21. We demonstrate that joint initialization, projective readout and fast local and non-local gate operations can all be achieved in diamond spin systems, even under ambient conditions. High-fidelity initialization of a whole spin register (99 per cent) and single-shot readout of multiple individual nuclear spins are achieved by using the ancillary electron spin of a nitrogen-vacancy defect. Implementation of a novel non-local gate generic to our electron-nuclear quantum register allows the preparation of entangled states of three nuclear spins, with fidelities exceeding 85 per cent. With these techniques, we demonstrate three-qubit phase-flip error correction. Using optimal control, all of the above operations achieve fidelities approaching those needed for fault-tolerant quantum operation, thus paving the way to large-scale quantum computation. Besides their use with diamond spin systems, our techniques can be used to improve scaling of quantum networks relying on phosphorus in silicon.sup.19, quantum dots.sup.22, silicon carbide.sup.11 or rare-earth ions in solids.sup.20,21., Author(s): G. Waldherr [sup.1] , Y. Wang [sup.1] , S. Zaiser [sup.1] , M. Jamali [sup.1] , T. Schulte-Herbrüggen [sup.2] , H. Abe [sup.3] , T. Ohshima [sup.3] , J. [...]

From sequences of speech sounds 1,2 or letters 3 , humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing 4-12 , the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words' meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension., (© 2024. The Author(s).)

Humans are capable of generating extraordinarily diverse articulatory movement combinations to produce meaningful speech. This ability to orchestrate specific phonetic sequences, and their syllabification and inflection over subsecond timescales allows us to produce thousands of word sounds and is a core component of language 1,2 . The fundamental cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh-density Neuropixels recordings capable of sampling across the cortical column in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events before utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also accurately predicted the phonetic, syllabic and morphological components of upcoming words and showed a temporally ordered dynamic. Collectively, we show how these mixtures of cells are broadly organized along the cortical column and how their activity patterns transition from articulation planning to production. We also demonstrate how these cells reliably track the detailed composition of consonant and vowel sounds during perception and how they distinguish processes specifically related to speaking from those related to listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and demonstrate a cellular process that can support the production of speech., (© 2024. The Author(s).)

Human social behaviour crucially depends on our ability to reason about others. This capacity for theory of mind has a vital role in social cognition because it enables us not only to form a detailed understanding of the hidden thoughts and beliefs of other individuals but also to understand that they may differ from our own 1-3 . Although a number of areas in the human brain have been linked to social reasoning 4,5 and its disruption across a variety of psychosocial disorders 6-8 , the basic cellular mechanisms that underlie human theory of mind remain undefined. Here, using recordings from single cells in the human dorsomedial prefrontal cortex, we identify neurons that reliably encode information about others' beliefs across richly varying scenarios and that distinguish self- from other-belief-related representations. By further following their encoding dynamics, we show how these cells represent the contents of the others' beliefs and accurately predict whether they are true or false. We also show how they track inferred beliefs from another's specific perspective and how their activities relate to behavioural performance. Together, these findings reveal a detailed cellular process in the human dorsomedial prefrontal cortex for representing another's beliefs and identify candidate neurons that could support theory of mind.