Biology subjects

Laje, R.

Publications and source records attributed to Laje, R..

4 recordsLinked to original sources

bioRxiv2023

Cross-homeostatic plasticity enables analog neuromorphic circuits to exhibit robust computational primitives

AbstractMany neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits that use the physics of silicon to emulate neuronal dynamics represent a promising approach for implementing the brains computational primitives, including self-sustained neural activity. However, achieving the same robustness of biological networks in neuromorphic computing systems remains a challenge, due to the high degree of heterogeneity and variability of their analog components. Inspired by the strategies used by real cortical networks, we apply a biologically-plausible cross-homeostatic learning rule to balance excitation and inhibition in neuromorphic implementations of spiking recurrent neural networks. We demonstrate how this learning rule allows the neuromorphic system to work in the presence of device mismatch and to autonomously tune the spiking network to produce robust, self-sustained, fixed-point attractor dynamics with irregular spiking in an inhibition-stabilized regime. We show that this rule can implement multiple, coexisting stable memories, with emergent soft-winner-take-all (sWTA) dynamics, and reproduce the so-called "paradoxical effect" widely observed in cortical circuits. In addition to validating neuroscience models on a substrate that shares many similar properties and limitations with biological systems, this work enables the construction of ultra-low power, mixed-signal neuromorphic technologies that can be automatically configured to compute reliably, despite the large on-chip and chip-to-chip variability of their analog components.

neuroscience↗

bioRxiv2021

Time-oriented attention improves accuracy in a paced finger tapping task

Finger tapping is a task widely used in a variety of experimental paradigms, in particular to understand sensorimotor synchronization and time processing in the range of hundreds of milliseconds (millisecond timing). Normally, subjects dont receive any instruction about what to attend to and the results are seldom interpreted taking into account the possible effects of attention. In this work we show that attention can be oriented to the purely temporal aspects of a paced finger tapping task and that it affects performance. Specifically, time-oriented attention improves the accuracy in paced finger tapping and it also increases the resynchronization efficiency after a period perturbation. We use two markers of the attention level: auditory ERPs and subjective report of the mental workload. In addition, we propose a novel algorithm to separate the auditory, stimulus-related components from the somatosensory, response-related ones, which are naturally overlapped in the recorded EEG.

neuroscience↗

bioRxiv2021

Orchestrated Excitatory and Inhibitory Learning Rules Lead to the Unsupervised Emergence of Up-states and Balanced Network Dynamics

Self-sustaining neural activity maintained through local recurrent connections is of fundamental importance to cortical function. We show that Up-states--an example of self-sustained, inhibition-stabilized network dynamics--emerge in cortical circuits across three weeks of ex vivo development, establishing the presence of unsupervised learning rules capable of generating self-sustained dynamics. Previous computational models have established that four sets of weights (WE[<-]E, WE[<-]I, WI[<-]E, WI[<-]I) must interact in an orchestrated manner to produce Up-states, but have not addressed how a family of learning rules can operate in parallel at all four weight classes to generate self-sustained inhibition-stabilized dynamics. Using numerical and analytical methods we show that, in part due to the paradoxical effect, standard homeostatic rules are only stable in a narrow parameter regime. In contrast, we show that a family of biologically plausible learning rules based on "cross-homeostatic" plasticity robustly lead to the emergence of self-sustained, inhibition-stabilized dynamics.

neuroscience↗

bioRxiv2019

Temporal and spatiotemporal perturbations in paced finger tapping point to a common mechanism for the processing of time errors

Paced finger tapping is a sensorimotor synchronization task where a subject is instructed to keep pace with an external metronome, as when following along with the beat of music, and the time differences (asynchronies) between each stimulus and its response are recorded. The usual way to study the underlying error correction mechanism is to make unexpected temporal perturbations to the stimuli sequence and then let the subject recover average synchronization. A critical but overlooked issue in traditional temporal perturbations, however, is that at the moment of perturbation two things change: both the stimuli period (a parameter) and the asynchrony (a variable). In terms of experimental manipulation, it would be desirable to have separate, independent control of parameter and variable values. In this work we perform paced finger tapping experiments combining simple temporal perturbations (tempo step change) and spatial perturbations with temporal effect (raised or lowered point of contact). In this way we decouple the parameter-and-variable confounding of traditional temporal perturbations and perform novel perturbations where either the parameter only changes or the variable only changes. Our results show nonlinear features like asymmetry and are compatible with the idea of a common mechanism for the correction of all types of asynchronies. We suggest taking this confounding into account when analyzing perturbations of any kind in finger tapping tasks but also in other areas of sensorimotor synchronization, like music performance experiments and paced walking in gait coordination studies.

neuroscience↗