Miracle-dz/UniFAR-FTUs huggingface dataset:
Inter and Intralaminar Excitation of Parvalbumin Interneurons in Mouse Barrel Cortex

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition, control rhythmic activity, and have been linked to disorders including autism spectrum and schizophrenia. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes simultaneously in many L2/3 and L4 PV interneurons to stimulation in either L2/3 or L4. Decay-times were consistent across L2/3 and L4. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus PV interneurons in different cortical layers of BC show differences in response properties with potential roles in cortical computations. Key points summary Excitatory synaptic responses were imaged in parvalbumin (PV) interneurons in slices of mouse barrel cortex using a targeted genetically-encoded voltage sensor. This approach revealed simultaneous voltage changes in approximately 20 neurons pre slice in response to stimulation. PV interneurons residing in layer 2/3 had larger amplitudes, longer half-widths, and longer rise-times than PV interneurons residing in layer 4. Responses of PV interneurons residing in either layer 2/3 or layer 4 had shorter latencies to stimulation of layer 4 compared to stimulation of layer 2/3. Excitatory synaptic transmission to PV interneurons varies with layer of residence and source of excitation.
Morphological brain networks of white matter: mapping, evaluation, characterization and application

Neuroimaging-based connectomics studies have long focused on the wiring patterns between gray matter regions. In recent years, increasing evidence emerges that neural activity in specific sets of white matter (WM) tracts dynamically fluctuates in a coordinated manner. However, the structural basis underlying the coordination is poorly understood largely due to the lack of approaches for estimating structural relations between WM regions. Here, we developed an approach to construct morphological WM networks based on structural magnetic resonance imaging. We found that the morphological WM networks exhibited nontrivial organizational principles, presented good to excellent short- and long-term reliability, accounted for phenotypic interindividual differences (Motor and Cognition), and were under genetic control. Interestingly, highly heritable edges contributed largely to interindividual differences in phenotype. Through integration with other multimodal and multiscale data, we further showed that the morphological WM networks were able to predict regional profiles of hamodynamic coherence, metabolic synchronization, gene co-expression and chemoarchitectonic covariance. Moreover, the prediction followed functional connectomic hierarchy of WM for hamodynamic coherence, was driven by genes enriched in the forebrain neuron development and differentiation for gene co-expression, and was attributed to serotonergic system-related receptors and transporters for chemoarchitectonic covariance. Finally, applying our approach to multiple sclerosis and neuromyelitis optica spectrum disorders, we found that both diseases were associated with morphological WM dysconnectivity, which was correlated with clinical variables and able to diagnose and differentiate the diseases. Altogether, our findings indicate that morphological WM networks provide a reliable and meaningful means to explore WM architecture in health and disease.
The Holochronous Universe: Time to Shed Some Light on the Dark Sector?

We describe a novel interpretation of the time dimension in General Relativity: the Holochronous Principle, and show that the application of this principle in standard cosmological situations is able fully to account for the effects currently attributed to Dark Matter in observational phenomena such as galactic rotation curves and gravitational lensing. We re-evaluate the role of the Friedman equations in defining a time varying spacetime metric, and in their place postulate a model that is based on the `shrinkage' of baryons in a gravitational field to account for the dynamical behaviour of the cosmic scale factor. We show that integrating the Holochronous Principle into this model gives rise to a solution that takes the form of a resonant universe, in which the resultant damped oscillations can account for the observed accelerating expansion rate of the universe, to a greater level of precision than the standard ΛCDM model. The Holochronous model obviates the need for Dark Energy in the form of a cosmological constant, Λ, and also resolves other issues associated with the ΛCDM model, including the Ω=1 flatness problem.
The ghrelin receptor GHSR has two efficient agonists in an ancient fish species

The gastric peptide ghrelin and its receptor GHSR have important functions in energy metabolism. Recently, liver-expressed antimicrobial peptide 2 (LEAP2) was identified as an endogenous antagonist for GHSR. Ghrelin, LEAP2, and GHSR are ubiquitously present from fishes to mammals and are highly conserved in evolution. However, our recent study suggested that GHSRs from the Actinopterygii fish Danio rerio (zebrafish) and Larimichthys crocea (large yellow croaker) have lost their binding to ghrelin, despite binding normally to LEAP2. Do these fish GHSRs use another peptide as their agonist? To answer this question, in the present study, we tested to two fish motilins that are closely related to ghrelin. In ligand binding and activation assays, the fish GHSRs from D. rerio and L. crocea displayed no detectable or very low binding to all tested motilins; however, the GHSR from the Sarcopterygii fish Latimeria chalumnae (coelacanth) bound to its motilin with high affinity and was efficiently activated by it. Therefore, it seemed that motilin is not a ligand for GHSR in D. rerio and L. crocea, but is an efficient agonist for GHSR in L. chalumnae, which is known as a ‘living fossil’ and is believed to be one of the closest fish ancestors of tetrapods. The results of present study suggested that in ancient fishes, GHSR had two efficient agonists, ghrelin and motilin; however, this feature might be only preserved in some extant fishes with ancient evolutionary origins. Our present work shed new light on the ligand usage of GHSR in different fish species and in evolution.
Demonstration that sublinear dendrites enable linearly non-separable computations

Theory predicts that nonlinear summation of synaptic potentials within dendrites allows neurons to perform linearly non-separable computations (LNSCs). Using Boolean analysis approaches, we predicted that both supralinear and sublinear synaptic summation could allow single neurons to implement a type of LNSC, the feature binding problem (FBP), which does not require inhibition contrary to the XOR. Notably, sublinear dendritic operations enable LNSCs when scattered synaptic activation generates increased somatic spike output. However, experimental demonstrations of scatter-sensitive neuronal computations have not yet been described. Using glutamate uncaging onto cerebellar molecular layer interneurons, we show that scattered synaptic-like activation of dendrites evoked larger compound EPSPs than clustered synaptic activation, generating a higher output spiking probability. Moreover, we also demonstrate that single interneurons can indeed implement the FBP. We use a biophysical model to predict under what conditions a neuron can implement the FBP and what leads to failures. Experimental results agree with the model-determined conditions and hence validate our protocol as a solid benchmark for a neuron to implement linearly non-separable computations. Since sublinear synaptic summation is a property of passive dendrites we expect that many different neuron types can implement LNSCs.
Differential encoding of temporal context and expectation under representational drift across hierarchically connected areas

The classic view that neural populations in sensory cortices preferentially encode responses to incoming stimuli has been strongly challenged by recent experimental studies. Despite the fact that a large fraction of variance of visual responses in rodents can be attributed to behavioral state and movements, trial-history, and salience, the effects of contextual modulations and expectations on sensory-evoked responses in visual and association areas remain elusive. Here, we present a comprehensive experimental and theoretical study showing that hierarchically connected visual and association areas differentially encode the temporal context and expectation of naturalistic visual stimuli, consistent with the theory of hierarchical predictive coding. We measured neural responses to expected and unexpected sequences of natural scenes in the primary visual cortex (V1), the posterior medial higher order visual area (PM), and retrosplenial cortex (RSP) using 2-photon imaging in behaving mice collected through the Allen Institute Mindscope’s OpenScope program. We found that information about image identity in neural population activity depended on the temporal context of transitions preceding each scene, and decreased along the hierarchy. Furthermore, our analyses revealed that the conjunctive encoding of temporal context and image identity was modulated by expectations of sequential events. In V1 and PM, we found enhanced and specific responses to unexpected oddball images, signaling stimulus-specific expectation violation. In contrast, in RSP the population response to oddball presentation recapitulated the missing expected image rather than the oddball image. These differential responses along the hierarchy are consistent with classic theories of hierarchical predictive coding whereby higher areas encode predictions and lower areas encode deviations from expectation. We further found evidence for drift in visual responses on the timescale of minutes. Although activity drift was present in all areas, population responses in V1 and PM, but not in RSP, maintained stable encoding of visual information and representational geometry. Instead we found that RSP drift was independent of stimulus information, suggesting a role in generating an internal model of the environment in the temporal domain. Overall, our results establish temporal context and expectation as substantial encoding dimensions in the visual cortex subject to fast representational drift and suggest that hierarchically connected areas instantiate a predictive coding mechanism.
A Note on a CBC-Type Mode of Operation

In this paper we formally introduce a novel mode of operation based on the cipher block chaining mode. The main idea of this mode is to use a stateful block cipher instead of a stateless one. Afterwards, we show how to implement our proposal and present a performance analysis of our mode. Next, we provide a concrete security analysis by computing a tight bound on the success of adversaries based on their resources. The results of our performance and security analyses are that this novel mode is more secure than the cipher block chaining mode for large files, but the encryption/decryption time doubles/triples. Therefore, our novel mode is suitable for encrypting large files, when higher security is required, but speed is not paramount. Note that the changes required to transform the software implementations of the cipher block chaining mode into this new mode are minimal, and therefore transitioning to this new mode is straightforward.
A Needle in the Haystack: Inspecting Circuit Layout to Identify Hardware Trojans

—Distributed integrated circuit (IC) supply chain has resulted in a myriad of security vulnerabilities including that of hardware Trojan (HT). An HT can perform malicious modifications on an IC design with potentially disastrous consequences, such as leaking secret information in cryptographic applications or altering operation instructions in processors. Due to the emergence of outsourced fabrication, an untrusted foundry is considered the most potent adversary in introducing an HT. This can be attributed to the asymmetric business model between the design house and the foundry; the design house is completely oblivious to the fabrication process, whereas the design IP is transparent to the foundry, thereby having full control over the layout. In order to address this issue, in this paper, we—for the first time—introduce a layout-level HT detection algorithm utilizing low-confidence classification and providing Trojan localization. We convert the IC layout to a graph and utilize Graph Neural Network (GNN)-based learning frameworks to flag any unrecognized suspicious region in the layout. The proposed framework is evaluated on AES and RS232 designs from the Trusthub benchmark suite, where it has been demonstrated to detect all nine HT-inserted designs. Finally, we open-source the full code-base for the research community at large [1].
FUSE – Flexible File Format and Intermediate Representation for Secure Multi-Party Computation

Secure Multi-Party Computation (MPC) is continuously becoming more and more practical. Many optimizations have been introduced, making MPC protocols more suitable for solving real-world problems. However, the MPC protocols and optimizations are usually implemented as a standalone proof of concept or in an MPC framework and are tightly coupled with special-purpose circuit formats, such as Bristol Format. This makes it very hard and time-consuming to re-use algorithmic advances and implemented applications in a different context. Developing generic algorithmic optimizations is exceptionally hard because the available MPC tools and formats are not generic and do not provide the necessary infrastructure. In this paper, we present FUSE: A Framework for Unifying and Optimizing Secure Multi-Party Computation Implementations with Efficient Circuit Storage. FUSE provides a flexible intermediate representation (FUSE IR) that can be used across different platforms and in different programming languages, including C/C++, Java, Rust, and Python. We aim at making MPC tools more interoperable, removing the tight coupling between high-level compilers for MPC and specific MPC protocol engines, thus driving knowledge transfer. Our framework is inspired by the widely known LLVM compiler framework. FUSE is portable, extensible, and it provides implementation-agnostic optimizations. As frontends, we implement HyCC (CCS’18), the Bristol circuit format, and MOTION (TOPS’22), s.t. these can be automatically converted to FUSE IR. We implement several generic optimization passes, such as automatic subgraph replacement and vectorization, to showcase the utility and efficiency of our framework. Finally, we implement as backends MOTION and MP-SPDZ (CCS’20), so that FUSE IR can be run by these frameworks in an MPC protocol, as well as other useful backends for JSON output and the DOT language for graph visualization. With FUSE, it is possible to use any implemented frontend with any implemented backend and vice-versa. FUSE IR is not only efficient to work on and much more generic than any other format so far – supporting, e.g., function calls, hybrid MPC protocols as well as user-defined building blocks, and annotations – while maintaining backwards-compatibility, but also compact, with smaller storage size than even minimalistic formats such as Bristol already for a few hundred operations.
Abraxas: Throughput-Efficient Hybrid Asynchronous Consensus

Protocols for state-machine replication (SMR) often trade off performance for resilience to network delay. In particular, protocols for asynchronous SMR tolerate arbitrary network delay but sacrifice throughput/latency when the network is fast, while partially synchronous protocols have good performance in a fast network but fail to make progress if the network experiences high delay. Existing hybrid protocols are resilient to arbitrary network delay and have good performance when the network is fast, but suffer from high overhead (''thrashing'') if the network repeatedly switches between being fast and slow, e.g., in a network that is typically fast but has intermittent message delays. We propose Abraxas, a generic approach for constructing a hybrid protocol from any ''fast'' protocol Πfast and asynchronous protocolΠslow to achieve (1) security and performance equivalent to Πslow under arbitrary network behavior, and (2) performance equivalent to Πfast when conditions are favorable. We instantiate Abraxas with the best existing protocols for Πfast (Jolteon) and Πslow (\mbox2-chain VABA), and show experimentally that the resulting protocol significantly outperforms Ditto, the previous state-of-the-art hybrid protocol.
SEC: Fast Private Boolean Circuit Evaluation from Encrypted Look-ups

Encrypted computation has over the past thirty years, turned into one of the holy grails of modern cryptography especially with the advent of cloud computing. Modern cryptographic techniques like Fully Homomorphic Encryption (FHE) allow arbitrary Boolean circuit evaluation with encrypted inputs. However, the prohibitively high computation and storage overhead coupled with high communication bandwidth of FHE severely limit its scalability in practical applications like real-time analytics or machine learning inference. In summary, the current cryptographic literature lacks robust and scalable methods for efficient encrypted computation in practical outsourced applications. Inthiswork, we introduce a new approach for encrypted computation called SEC (Symmetric Encryption-based Computation) which offers fast Boolean circuit evaluation with optimal storage and communication overhead while scaling smoothly to real applications. SEC relies on an efficient Searchable Symmetric Encryption (SSE) construction to leverage the power of encrypted lookups in Boolean circuit evaluation. SEC is specifically suited for client-server systems, and the server, honest-but-curious receives the client’s encrypted inputs and outputs the encrypted evaluation result while leaking only benign information to the server. SEC essentially extends the capabilities of SSE schemes from searching over encrypted databases to arbitrary function evaluation over encrypted inputs. SEC supports Boolean function composition, allowing it to evaluate complex functions efficiently without blowing up storage overhead. SEC outperforms the state-of-the-art FHE, namely, Torus FHE (TFHE) scheme with an average 10 3 × speed-up in basic Boolean gate evaluations. We present a prototype implementation of SEC and experimentally validate its practical efficiency. Our experiments show that SEC executes arbitrary depth Boolean circuit in a single round of communication between client and server with a significant improvement in performance than the fastest TFHE backends. We exemplify the applicability of our scheme by implementing one byte AES SBox using SEC and comparing the results with TFHE.
Secret Swapping: Two Party Fair Exchange

Consider two participants who wish to each reveal some secret information to each other, but both will only reveal their secret if there is a guarantee that the other will do so too. Conventionally, whoever sends their secret ﬁrst makes themselves vulnerable to the possibility that the other party will cheat and won’t send their secret in reply. Fair Exchange (FE) protocols are a class of cryptographic construction which allow an exchange like this to occur without either party making themselves vulnerable. It is widely believed that a trusted third party arbitrator is required to intervene in the case of a dispute. We present a FE protocol that allows two parties to exchange secrets, safe in the knowledge that either both secrets will be exchanged, or neither will; without the involvement of a third party. This construction requires that the parties run online interactive processes, with reasonable timeliness requirements on the messages. In this work we provide a scheme for swapping arbitrarily sized secrets with security that reduces to the strength of an underlying symmetric authenticated encryption scheme.
ON THE COMPUTATION OF WIND FROM PRESSURE DATA

Abstract From a statistical analysis of geostrophic- and gradient-wind computations for all stations reporting winds on two 700-mb charts, it is shown that there is a variability of about 25 per cent in the computations by different individuals, and that the computed values differed by about 35 per cent from the observed wind speed on the average. The percentual deviation was smaller for strong winds. The gradient wind computed. using approximate trajectory curvature was only slightly better than the geostrophic, and using contour curvature it was worse. The geostrophic wind thus appears to be the best approximation which can be computed from the pressure field alone. Theoretical expressions for the deviations of the computed from the observed speeds and velocities are derived. These show that the gradient speed is always greater than the true speed. The gradient speed is of shown to be a better approximation than the geostrophic for most cases, but for some cases of curved cross-isobaric flow the geostro.
A Two-Party Hierarchical Deterministic Wallets in Practice

The applications of Hierarchical Deterministic Wallet are rapidly growing in various areas such as cryptocurrency exchanges and hardware wallets. Improving privacy and security is more important than ever. In this study, we proposed a protocol that fully support a two-party computation of BIP32. Our protocol, similar to the distributed key generation, can generate each party’s secret share, the common chain-code, and the public key without revealing a seed and any descendant private keys. We also provided a simulation-based proof of our protocol assuming a rushing, static, and malicious adversary in the hybrid model. Our master key generation protocol produces up to total of two bit leakages from a honest party given the feature that the seeds will be re-selected after each execution. The proposed hardened child key derivation protocol leads up to a one bit leakage in the worst situation of simulation from a honest party and will be accumulated with each execution. Fortunately, in reality, this issue can be largely mitigated by adding some validation criteria of boolean circuits and masking the input shares before each execution. We then implemented the proposed protocol and ran in a single thread on a laptop which turned out with practically acceptable execution time. Lastly, the outputs of our protocol can be easily integrated with many threshold sign protocols.