The Impact of Stimulation Induced Short-Term Synaptic Plasticity on Firing Patterns in the Globus Pallidus of the Rat

Electrical stimulation in the globus pallidus (GP) leads to complex modulations of neuronal activity in the stimulated nucleus. Multiple in vivo studies have demonstrated the modulation of both firing rates and patterns during and immediately following the GP stimulation. Previous in vitro studies, together with computational studies, have suggested the involvement of short-term synaptic plasticity (STP) during the stimulation. The aim of the current study was to explore in vitro the effects of STP on neuronal activity of GP neurons during local repetitive stimulation. We recorded synaptic potentials and assessed the modulations of spontaneous firing in a postsynaptic neuron in acute brain slices via a whole-cell pipette. Low-frequency repetitive stimulation locked the firing of the neuron to the stimulus. However, high-frequency repetitive stimulation in the GP generated a biphasic modulation of the firing frequency consisting of inhibitory and excitatory phases. Using blockers of synaptic transmission, we show that GABAergic synapses mediated the inhibitory and glutamatergic synapses the excitatory part of the response. Furthermore, we report that at high stimulation frequencies both types of synapses undergo short-term depression leading to a time dependent modulation of the neuronal firing. These findings indicate that STP modulates the dynamic responses of pallidal activity during electrical stimulation, and may contribute to a better understanding of the mechanism underlying deep brain stimulation like protocols

Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding

Grokking is the intriguing phenomenon where a model learns to generalize long after it has fit the training data. We show both analytically and numerically that grokking can surprisingly occur in linear networks performing linear tasks in a simple teacher-student setup with Gaussian inputs. In this setting, the full training dynamics is derived in terms of the training and generalization data covariance matrix. We present exact predictions on how the grokking time depends on input and output dimensionality, train sample size, regularization, and network initialization. We demonstrate that the sharp increase in generalization accuracy may not imply a transition from "memorization" to "understanding", but can simply be an artifact of the accuracy measure. We provide empirical verification for our calculations, along with preliminary results indicating that some predictions also hold for deeper networks, with non-linear activations.Comment: 17 pages, 6 figure

Fast Structuring of Radio Networks for Multi-Message Communications

We introduce collision free layerings as a powerful way to structure radio networks. These layerings can replace hard-to-compute BFS-trees in many contexts while having an efficient randomized distributed construction. We demonstrate their versatility by using them to provide near optimal distributed algorithms for several multi-message communication primitives. Designing efficient communication primitives for radio networks has a rich history that began 25 years ago when Bar-Yehuda et al. introduced fast randomized algorithms for broadcasting and for constructing BFS-trees. Their BFS-tree construction time was $O(D \log^2 n)$ rounds, where $D$ is the network diameter and $n$ is the number of nodes. Since then, the complexity of a broadcast has been resolved to be $T_{BC} = \Theta(D \log \frac{n}{D} + \log^2 n)$ rounds. On the other hand, BFS-trees have been used as a crucial building block for many communication primitives and their construction time remained a bottleneck for these primitives. We introduce collision free layerings that can be used in place of BFS-trees and we give a randomized construction of these layerings that runs in nearly broadcast time, that is, w.h.p. in $T_{Lay} = O(D \log \frac{n}{D} + \log^{2+\epsilon} n)$ rounds for any constant $\epsilon>0$. We then use these layerings to obtain: (1) A randomized algorithm for gathering $k$ messages running w.h.p. in $O(T_{Lay} + k)$ rounds. (2) A randomized $k$-message broadcast algorithm running w.h.p. in $O(T_{Lay} + k \log n)$ rounds. These algorithms are optimal up to the small difference in the additive poly-logarithmic term between $T_{BC}$ and $T_{Lay}$. Moreover, they imply the first optimal $O(n \log n)$ round randomized gossip algorithm

MPC for Tech Giants (GMPC): Enabling Gulliver and the Lilliputians to Cooperate Amicably

In this work, we introduce the Gulliver multi-party computation model (GMPC). The GMPC model considers a single highly powerful party, called the server or Gulliver, that is connected to $n$ users over a star topology network (alternatively formulated as a full network, where the server can block any message). The users are significantly less powerful than the server, and, in particular, should have both computation and communication complexities that are polylogarithmic in $n$. Protocols in the GMPC model should be secure against malicious adversaries that may corrupt a subset of the users and/or the server. Designing protocols in the GMPC model is a delicate task, since users can only hold information about polylog(n) other users (and, in particular, can only communicate with polylog(n) other users). In addition, the server can block any message between any pair of honest parties. Thus, reaching an agreement becomes a challenging task. Nevertheless, we design generic protocols in the GMPC model, assuming that at most $\alpha<1/6$ fraction of the users may be corrupted (in addition to the server). Our main contribution is a variant of Feige's committee election protocol [FOCS 1999] that is secure in the GMPC model. Given this tool we show: 1. Assuming fully homomorphic encryption (FHE), any computationally efficient function with $O\left(n\cdot polylog(n)\right)$-size output can be securely computed in the GMPC model. 2. Any function that can be computed by a circuit of $O(polylog(n))$ depth, $O\left(n\cdot polylog(n)\right)$ size, and bounded fan-in and fan-out can be securely computed in the GMPC model without assuming FHE. 3. In particular, sorting can be securely computed in the GMPC model without assuming FHE. This has important applications for the shuffle model of differential privacy, and resolves an open question of Bell et al. [CCS 2020]

On Secure Computation of Solitary Output Functionalities With and Without Broadcast

Solitary output secure computation models scenarios, where a single entity wishes to compute a function over an input that is distributed among several mutually distrusting parties. The computation should guarantee some security properties, such as correctness, privacy, and guaranteed output delivery. Full security captures all these properties together. This setting is becoming very important, as it is relevant to many real-world scenarios, such as service providers wishing to learn some statistics on the private data of their users. In this paper, we study full security for solitary output three-party functionalities in the point-to-point model (without broadcast) assuming at most a single party is corrupted. We give a characterization of the set of three-party Boolean functionalities and functionalities with up to three possible outputs (over a polynomial-size domain) that are computable with full security in the point-to-point model against a single corrupted party. We also characterize the set of three-party functionalities (over a polynomial-size domain) where the output receiving party has no input. Using this characterization, we identify the set of parameters that allow certain functionalities related to private set intersection to be securely computable in this model. Our main technical contribution is a reinterpretation of the hexagon argument due to Fischer et al. [Distributed Computing \u2786]. While the original argument relies on the agreement property (i.e., all parties output the same value) to construct an attack, we extend the argument to the solitary output setting, where there is no agreement. Furthermore, using our techniques, we were also able to advance our understanding of the set of solitary output three-party functionalities that can be computed with full security, assuming broadcast but where two parties may be corrupted. Specifically, we extend the set of such functionalities that were known to be computable, due to Halevi et al. [TCC \u2719]

On perfectly secure 2PC in the OT-hybrid model

A well known result by Kilian (ACM 1988) asserts that general secure two computation (2PC) with statistical security, can be based on OT. Specifically, in the client-server model, where only one party -- the client -- receives an output, Kilian’s result shows that given the ability to call an ideal oracle that computes OT, two parties can securely compute an arbitrary function of their inputs with unconditional security. Ishai et al. (EUROCRYPT 2011) further showed that this can be done efficiently for every two-party functionality in $\mathrm{NC}^1$ in a single round. However, their results only achieve statistical security, namely, it is allowed to have some error in security. This leaves open the natural question as to which client-server functionalities can be computed with perfect security in the OT-hybrid model, and what is the round complexity of such computation. So far, only a handful of functionalities were known to have such protocols. In addition to the obvious theoretical appeal of the question towards better understanding secure computation, perfect, as opposed to statistical reductions, may be useful for designing secure multiparty protocols with high concrete efficiency, achieved by eliminating the dependence on a security parameter. In this work, we identify a large class of client-server functionalities $f:\mathcal{X}\times \mathcal{Y}\mapsto \{0,1\}$, where the server\u27s domain $\mathcal{X}$ is larger than the client\u27s domain $\mathcal{Y}$, that have a perfect reduction to OT. Furthermore, our reduction is 1-round using an oracle to secure evaluation of many parallel invocations of $\binom21$-bit-OT, as done by Ishai et al. (EUROCRYPT 2011). Interestingly, the set of functions that we are able to compute was previously identified by Asharov (TCC 2014) in the context of fairness in two-party computation, naming these functions full-dimensional. Our result also extends to randomized non-Boolean functions $f:\mathcal{X}\times \mathcal{Y}\mapsto\{0,\ldots,k-1\}$ satisfying $|\mathcal{X}|>(k-1)\cdot|\mathcal{Y}|$

Broadcasting in Noisy Radio Networks

The widely-studied radio network model [Chlamtac and Kutten, 1985] is a graph-based description that captures the inherent impact of collisions in wireless communication. In this model, the strong assumption is made that node $v$ receives a message from a neighbor if and only if exactly one of its neighbors broadcasts. We relax this assumption by introducing a new noisy radio network model in which random faults occur at senders or receivers. Specifically, for a constant noise parameter $p \in [0,1)$, either every sender has probability $p$ of transmitting noise or every receiver of a single transmission in its neighborhood has probability $p$ of receiving noise. We first study single-message broadcast algorithms in noisy radio networks and show that the Decay algorithm [Bar-Yehuda et al., 1992] remains robust in the noisy model while the diameter-linear algorithm of Gasieniec et al., 2007 does not. We give a modified version of the algorithm of Gasieniec et al., 2007 that is robust to sender and receiver faults, and extend both this modified algorithm and the Decay algorithm to robust multi-message broadcast algorithms. We next investigate the extent to which (network) coding improves throughput in noisy radio networks. We address the previously perplexing result of Alon et al. 2014 that worst case coding throughput is no better than worst case routing throughput up to constants: we show that the worst case throughput performance of coding is, in fact, superior to that of routing -- by a $\Theta(\log(n))$ gap -- provided receiver faults are introduced. However, we show that any coding or routing scheme for the noiseless setting can be transformed to be robust to sender faults with only a constant throughput overhead. These transformations imply that the results of Alon et al., 2014 carry over to noisy radio networks with sender faults.Comment: Principles of Distributed Computing 201

Optimal competitiveness for the Rectilinear Steiner Arborescence problem

We present optimal online algorithms for two related known problems involving Steiner Arborescence, improving both the lower and the upper bounds. One of them is the well studied continuous problem of the {\em Rectilinear Steiner Arborescence} ($RSA$). We improve the lower bound and the upper bound on the competitive ratio for $RSA$ from $O(\log N)$ and $\Omega(\sqrt{\log N})$ to $\Theta(\frac{\log N}{\log \log N})$, where $N$ is the number of Steiner points. This separates the competitive ratios of $RSA$ and the Symetric-$RSA$, two problems for which the bounds of Berman and Coulston is STOC 1997 were identical. The second problem is one of the Multimedia Content Distribution problems presented by Papadimitriou et al. in several papers and Charikar et al. SODA 1998. It can be viewed as the discrete counterparts (or a network counterpart) of $RSA$. For this second problem we present tight bounds also in terms of the network size, in addition to presenting tight bounds in terms of the number of Steiner points (the latter are similar to those we derived for $RSA$)