Biology subjects

Harnett, M. T.

Publications and source records attributed to Harnett, M. T..

9 recordsLinked to original sources

bioRxiv2025

Plateau potentials are instructive signals for behavioral timescale synaptic plasticity in the neocortex

Learning occurs via the adjustment of synaptic weights across a variety of timescales. The mechanisms supporting these processes, from single-shot to iterative learning, are unclear. The prevailing model in the neocortex, spike-timing dependent plasticity (STDP), requires many pairings of precisely coordinated activity. This is difficult to reconcile with single-shot learning in behaving animals. In hippocampus, an alternative form of plasticity driven by plateau potentials (behavioral timescale synaptic plasticity; BTSP) alters synaptic weights in a single trial to reorganize spatial representations. Here we show that layer 5 pyramidal neurons (L5 PNs) of mouse primary visual cortex (V1) exhibit highly prevalent plateau potentials that drive single-shot changes in sensory representations. Spontaneously occurring and experimentally induced plateaus rapidly and persistently modified L5 PN responses to visual stimuli. In acute slices, plateau potentials drove synapse-specific plasticity with few repetitions across seconds-long pairing intervals. Our results demonstrate that plateau potentials in the neocortex rapidly reshape neuronal representations through BTSP. This instructive form of plasticity provides a mechanism for dynamic adjustment of neocortical synaptic weights to support rapid learning.

neuroscience↗

bioRxiv2025

CLOOSE: An open-source platform for optical closed-loop experiments

Brain-Computer Interfaces (BCI) have catalyzed advancements in both clinical applications and basic neuroscience research. However, technical barriers such as steep learning curves and complex synchronization requirements often impede their widespread adoption. In response to the increasing demand for optical BCI experiments and to the technical challenges associated with their implementation, we introduce CLOOSE (Closed-loop Optical Open-Source Experiments), a versatile platform designed to standardize, simplify, and accelerate closed-loop experiments with functional imaging data. CLOOSE interfaces easily with any frame-based imaging system via TCP/IP, allowing for real-time data streaming and distributed computation. Benchmark tests validate CLOOSEs real-time accuracy in image registration, signal processing, and analysis at imaging frequencies [≥]1 kHz, making it the first optical BCI compatible with voltage indicators. Throughout the paper we showcase CLOOSEs versatility in supporting several neurofeedback paradigms: from single neuron to population dynamics, multiplane imaging, and online (and offline) z-tracking. CLOOSEs functionality is easily accessible to users with minimal coding experience through an intuitive graphical interface for experiment setup and real-time performance monitoring. By significantly lowering the barrier to performing technically demanding closed-loop experiments, CLOOSE advances the streamlining, standardization, and democratization of online image analysis and neurofeedback BCI paradigms, opening new avenues for precise manipulation and real-time readout of neuronal activity in health and disease.

neuroscience↗

bioRxiv2024

Learning to use landmarks for navigation amplifies their representation in retrosplenial cortex

Visual landmarks provide powerful reference signals for efficient navigation by altering the activity of spatially tuned neurons, such as place cells, head direction cells, and grid cells. To understand the neural mechanism by which landmarks exert such strong influence, it is necessary to identify how these visual features gain spatial meaning. In this study, we characterized visual landmark representations in mouse retrosplenial cortex (RSC) using chronic two-photon imaging of the same neuronal ensembles over the course of spatial learning. We found a pronounced increase in landmark-referenced activity in RSC neurons that, once established, remained stable across days. Changing behavioral context by uncoupling treadmill motion from visual feedback systematically altered neuronal responses associated with the coherence between visual scene flow speed and self-motion. To explore potential underlying mechanisms, we modeled how burst firing, mediated by supralinear somatodendritic interactions, could efficiently mediate context- and coherence-dependent integration of landmark information. Our results show that visual encoding shifts to landmark-referenced and context-dependent codes as these cues take on spatial meaning during learning.

neuroscience↗

bioRxiv2023

A unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior

Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge, we developed ONIX, an open-source data acquisition system with high data throughput (2GB/sec) and low closed-loop latencies (<1ms) that uses a novel 0.3 mm thin tether to minimize behavioral impact. Head position and rotation are tracked in 3D and used to drive active commutation without torque measurements. ONIX can acquire from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, 3D-trackers, and other data sources. We used ONIX to perform uninterrupted, long ([~]7 hours) neural recordings in mice as they traversed complex 3-dimensional terrain. ONIX allowed exploration with similar mobility as non-implanted animals, in contrast to conventional tethered systems which restricted movement. By combining long recordings with full mobility, our technology will enable new progress on questions that require high-quality neural recordings during ethologically grounded behaviors.

neuroscience↗

bioRxiv2022

Coordinated Head Direction Representations in Mouse Anterodorsal Thalamic Nucleus and Retrosplenial Cortex

The sense of direction is critical for survival in changing environments and relies on flexibly integrating self-motion signals with external sensory cues. While the anatomical substrates involved in head direction (HD) coding are well known, the mechanisms by which visual information updates HD representations remain poorly understood. Retrosplenial cortex (RSC) plays a key role in forming coherent representations of space in mammals and it encodes a variety of navigational variables, including HD. Here, we use simultaneous two-area tetrode recording to show that RSC HD representation is nearly synchronous with that of the anterodorsal nucleus of thalamus (ADn), the obligatory thalamic relay of HD to cortex, during rotation of a prominent visual cue. Moreover, coordination of HD representations in the two regions is maintained during darkness. We further show that anatomical and functional connectivity are consistent with a strong feedforward drive of HD information from ADn to RSC, with surprisingly little reciprocal drive in the corticothalamic direction. Together, our results provide direct evidence for a concerted global HD reference update across cortex and thalamus, and establish the underlying functional connectivity that supports this coordination.

neuroscience↗

bioRxiv2022

Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex

From visual perception to language, sensory stimuli change their meaning depending on prior experience. Recurrent neural dynamics can interpret stimuli based on externally cued context, but it is unknown whether similar dynamics can compute and employ internal hypotheses to resolve ambiguities. Here, we show that mouse retrosplenial cortex (RSC) can form hypotheses over time and perform spatial reasoning through recurrent dynamics. In our task, mice navigated using ambiguous landmarks that are identified through their mutual spatial relationship, requiring sequential refinement of hypotheses. Neurons in RSC and in artificial neural networks encoded mixtures of hypotheses, location, and sensory information, and were constrained by robust low dimensional dynamics. RSC encoded hypotheses as locations in activity space with divergent trajectories for identical sensory inputs, enabling their correct interpretation. Our results indicate that interactions between internal hypotheses and external sensory data in recurrent circuits can provide a substrate for complex sequential cognitive reasoning.

neuroscience↗

bioRxiv2022

Dendritic compartmentalization of input-specific integration and plasticity rules across cortical development

Biological and artificial neural networks learn by modifying synaptic weights, but it is unclear how these systems can retain previous knowledge and also acquire new information. Here we show that cortical pyramidal neurons can solve this plasticity-versus-stability dilemma by differentially regulating synaptic plasticity at distinct dendritic compartments. Oblique dendrites of adult mouse layer 5b cortical pyramidal neurons selectively received monosynaptic thalamic input, integrated linearly, and-- surprisingly--lacked synaptic potentiation. In contrast, basal dendrites, which do not receive thalamic input, exhibited conventional NMDA receptor-mediated supralinear integration and synaptic potentiation. Congruently, spiny synapses on oblique branches showed low structural plasticity in vivo. A selective decline in NMDAR activity and expression at synapses on oblique dendrites was controlled by an experience-dependent critical period. Our results demonstrate a new biological mechanism for how single neurons can safeguard a set of inputs from ongoing plasticity by altering synaptic properties at distinct dendritic domains.

neuroscience↗

bioRxiv2021

The timescale and magnitude of aperiodic activity decreases with cortical depth in humans, macaques and mice

Cortical dynamics obey a 1/f power law, exhibiting an exponential decay of spectral power with increasing frequency. The slope and offset of this 1/f decay reflect the timescale and magnitude of aperiodic neural activity, respectively. These properties are tightly linked to cellular and circuit mechanisms (e.g. excitation:inhibition balance and firing rates) as well as cognitive processes (e.g. perception, memory, and state). However, the physiology underlying the 1/f power law in cortical dynamics is not well understood. Here, we compared laminar recordings from human, macaque and mouse cortex to evaluate how 1/f aperiodic dynamics vary across cortical layers and species. We report that 1/f slope is steepest in superficial layers and flattest in deep layers in each species. Additionally, the magnitude of this 1/f decay is greatest in superficial cortex and decreases with depth. We could account for both of these findings with a simple model in which superficial cortical transmembrane currents had longer time constants and greater densities than those in deeper layers. Together, our results provide novel insight into the organization of cortical dynamics, suggesting that the amplitude and time constant of local currents control circuit processing as a function of laminar depth. This may represent a general mechanism to facilitate appropriate integration of fast sensory inputs (infragranular) with slow feedback-type inputs (supragranular) across cortical areas and species.

neuroscience↗

bioRxiv2019

Twister3: a simple and fast microwire twister

We present Twister3, a microwire twisting machine. This device greatly increases the speed and repeatability of constructing twisted microwire neural probes (e.g. stereotrodes and tetrodes) compared to existing options. It is cheap, well documented, and all associated designs and source code are open-source. Twister3 is of interest to any lab performing twisted microwire neural recordings, for example, using tetrode drives.

neuroscience↗