Lesion studies have historically been instrumental for establishing causal connections between brain and behavior. They stand to provide additional insight if integrated with multielectrode techniques common in systems neuroscience. Here, we present and test a platform for creating electrolytic lesions through chronically implanted, intracortical multielectrode probes without compromising the ability to acquire neuroelectrophysiology. A custom-built current source provides stable current and allows for controlled, repeatable lesions in awake-behaving animals. Performance of this novel lesioning technique was validated using histology from ex vivo and in vivo testing, current and voltage traces from the device, and measurements of spiking activity before and after lesioning. This electrolytic lesioning method avoids disruptive procedures, provides millimeter precision over the extent and submillimeter precision over the location of the injury, and permits electrophysiological recording of single-unit activity from the remaining neuronal population after lesioning. This technique can be used in many areas of cortex, in several species, and theoretically with any multielectrode probe. The low-cost, external lesioning device can also easily be adopted into an existing electrophysiology recording setup. This technique is expected to enable future causal investigations of the recorded neuronal population\'s role in neuronal circuit function, while simultaneously providing new insight into local reorganization after neuron loss.
Over the past three decades, the field of neuroscience has made significant leaps in understanding how the brain works. This is largely thanks to microelectrode arrays, devices which are surgically implanted into the outermost layer of the brain known as the cortex. Once inserted, these devices can precisely monitor the electrical activity of a few hundred neurons while also stimulating neurons to reversibly modulate their activity. However, current microelectrode arrays are missing a key function: they cannot irreversibly inactivate neurons over long-time scales. This ability would allow researchers to understand how networks of neurons adapt and re-organize after injury or during neurodegenerative diseases where brain cells are progressively lost. To address this limitation, Bray, Clarke, et al. developed a device capable of creating consistent amounts of neuron loss, while retaining the crucial ability to record electrical activity following a lesion. Calibration tests in sheep and pigs provided the necessary parameters for this custom circuit, which was then verified as safe in non-human primates. These experiments demonstrated that the device could effectively cause neuron loss without compromising the recording capabilities of the microelectrode array. By seamlessly integrating neuron inactivation with monitoring of neuronal activity, scientists can now investigate the direct effects of such damage and subsequent neural reorganization. This device could help neuroscientists to explore neural repair and rehabilitation after brain cell loss, which may lead to better treatments for neurodegenerative diseases. In addition, this technique could offer insights into the interactions between neural circuits that drive behavior, enhancing our understanding of the complex mechanisms underlying how the brain works.

In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from the rodent medial prefrontal cortex [J. Henke et al., eLife10, e71612 (2021)] during an interval reproduction task and identified two cell groups by modeling their temporal receptive fields using hierarchical Bayesian models. The firing in the \"past cells\" group peaked at the start of the interval and relaxed exponentially back to baseline. The firing in the \"future cells\" group increased exponentially and peaked right before the planned action at the end of the interval. Contrary to the previous assumption that timing information in the brain has one or two time scales for a given interval, we found strong evidence for a continuous distribution of the exponential rate constants for both past and future cell populations. The real Laplace transformation of time predicts exponential firing with a continuous distribution of rate constants across the population. Therefore, the firing pattern of the past cells can be identified with the Laplace transform of time since the past event while the firing pattern of the future cells can be identified with the Laplace transform of time until the planned future event.

Since the spiking neural P system (SN P system) was proposed in 2006, it has become a research hotspot in the field of membrane computing. The SN P system performs computations through the encoding, processing, and transmission of spiking information and can be regarded as a third-generation neural network. As a variant of the SN P system, the global asynchronous numerical spiking neural P system (ANSN P system) is adaptable to a broader range of application scenarios. However, in biological neuroscience, some neurons work synchronously within a community to perform specific functions in the brain. Inspired by this, our work investigates a global asynchronous spiking neural P system (ANSN P system) that incorporates certain local synchronous neuron sets. Within these local synchronous sets, neurons must execute their production functions simultaneously, thereby reducing dependence on thresholds and enhancing control uncertainty in ANSN P systems. By analyzing the ADD, SUB, and FIN modules in the generating mode, as well as the INPUT and ADD modules in the accepting mode, this paper demonstrates the novel system\'s computational capacity as both a generator and an acceptor. Additionally, this paper compares each module to those in other SN P systems, considering the maximum number of neurons and rules per neuron. The results show that this new ANSN P system is at least as effective as the existing SN P systems.

Prior studies have documented the role of the striatum and its dopaminergic input in time processing, but the contribution of local striatal cholinergic innervation has not been specifically investigated. To address this issue, we recorded the activity of tonically active neurons (TANs), thought to be cholinergic interneurons in the striatum, in two male macaques performing self-initiated movements after specified intervals in the seconds range have elapsed. The behavioral data showed that movement timing was adjusted according to the temporal requirements. About one-third of all recorded TANs displayed brief depressions in firing in response to the cue that indicates the interval duration, and the strength of these modulations was, in some instances, related to the timing of movement. The rewarding outcome of actions also impacted TAN activity, as reflected by stronger responses to the cue paralleled by weaker responses to reward when monkeys performed correctly timed movements over consecutive trials. It therefore appears that TAN responses may act as a start signal for keeping track of time and reward prediction could be incorporated in this signaling function. We conclude that the role of the striatal cholinergic TAN system in time processing is embedded in predicting rewarding outcomes during timing behavior.

Prior studies have described the complex interplay that exists between glioma cells and neurons; however, the electrophysiological properties endogenous to glioma cells remain obscure. To address this, we employed Patch-sequencing (Patch-seq) on human glioma specimens and found that one-third of patched cells in IDH mutant (IDHmut) tumors demonstrate properties of both neurons and glia. To define these hybrid cells (HCs), which fire single, short action potentials, and discern if they are of tumoral origin, we developed the single cell rule association mining (SCRAM) computational tool to annotate each cell individually. SCRAM revealed that HCs possess select features of GABAergic neurons and oligodendrocyte precursor cells, and include both tumor and non-tumor cells. These studies characterize the combined electrophysiological and molecular properties of human glioma cells and describe a cell type in human glioma with unique electrophysiological and transcriptomic properties that may also exist in the non-tumor brain.

New memories are integrated into prior knowledge of the world. But what if consecutive memories exert opposing demands on the host brain network? We report that acquiring a robust (food-context) memory constrains the mouse hippocampus within a population activity space of highly correlated spike trains that prevents subsequent computation of a flexible (object-location) memory. This densely correlated firing structure developed over repeated mnemonic experience, gradually coupling neurons in the superficial sublayer of the CA1 stratum pyramidale to whole-population activity. Applying hippocampal theta-driven closed-loop optogenetic suppression to mitigate this neuronal recruitment during (food-context) memory formation relaxed the topological constraint on hippocampal coactivity and restored subsequent flexible (object-location) memory. These findings uncover an organizational principle for the peer-to-peer coactivity structure of the hippocampal cell population to meet memory demands.

Aging is a physiological process that is still poorly understood, especially with respect to effects on the brain. There are open questions about aging that are difficult to answer with an experimental approach. Underlying challenges include the difficulty of recording in vivo single cell and network activity simultaneously with submillisecond resolution, and brain compensatory mechanisms triggered by genetic, pharmacologic, or behavioral manipulations. Mathematical modeling can help address some of these questions by allowing us to fix parameters that cannot be controlled experimentally and investigate neural activity under different conditions. We present a biophysical minimal model of CA1 pyramidal cells (PCs) based on general expressions for transmembrane ion transport derived from thermodynamical principles. The model allows directly varying the contribution of ion channels by changing their number. By analyzing the dynamics of the model, we find parameter ranges that reproduce the variability in electrical activity seen in PCs. In addition, increasing the L-type Ca2+ channel expression in the model reproduces age-related changes in electrical activity that are qualitatively and quantitatively similar to those observed in PCs from aged animals. We also make predictions about age-related changes in PC bursting activity that, to our knowledge, have not been reported previously. We conclude that the model\'s biophysical nature, flexibility, and computational simplicity make it a potentially powerful complement to experimental studies of aging.

OBJECTIVE: Atrial fibrosis and autonomic remodelling are proposed pathophysiological mechanisms in atrial fibrillation (AF). Their impact on conduction velocity (CV) dynamics and wavefront propagation was evaluated.
RESULTS: Local activation times (LATs), voltage, and geometry data were obtained from patients undergoing ablation for persistent AF. LATs were obtained at three pacing intervals (PIs) in sinus rhythm (SR). LATs were used to determine CV dynamics and their relationship to local voltage amplitude. The impact of autonomic modulation- pharmacologically and with ganglionated plexi (GP) stimulation, on CV dynamics, wavefront propagation, and pivot points (change in wavefront propagation of ≥90°) was determined in SR. Fifty-four patients were included. Voltage impacted CV dynamics whereby at non-low voltage zones (LVZs) (≥0.5 mV) the CV restitution curves are steeper [0.03 ± 0.03 m/s ΔCV PI 600-400 ms (PI1), 0.54 ± 0.09 m/s ΔCV PI 400-250 ms (PI2)], broader at LVZ (0.2-0.49 mV) (0.17 ± 0.09 m/s ΔCV PI1, 0.25 ± 0.11 m/s ΔCV PI2), and flat at very LVZ (<0.2 mV) (0.03 ± 0.01 m/s ΔCV PI1, 0.04 ± 0.02 m/s ΔCV PI2). Atropine did not change CV dynamics, while isoprenaline and GP stimulation resulted in greater CV slowing with rate. Isoprenaline (2.7 ± 1.1 increase/patient) and GP stimulation (2.8 ± 1.3 increase/patient) promoted CV heterogeneity, i.e. rate-dependent CV (RDCV) slowing sites. Most pivot points co-located to RDCV slowing sites (80.2%). Isoprenaline (1.3 ± 1.1 pivot increase/patient) and GP stimulation (1.5 ± 1.1 increase/patient) also enhanced the number of pivot points identified.
CONCLUSIONS: Atrial CV dynamics is affected by fibrosis burden and influenced by autonomic modulation which enhances CV heterogeneity and distribution of pivot points. This study provides further insight into the impact of autonomic remodelling in AF.

In this study, we develop an in silico model of a neuron\'s behaviour under demyelination caused by a cytokine storm to investigate the effects of viral infections in the brain. We use a comprehensive model to measure how cytokine-induced demyelination affects the propagation of action potential (AP) signals within a neuron. We analysed the effects of neuron-neuron communications by applying information and communication theory at different levels of demyelination. Our simulations demonstrate that virus-induced degeneration can play a role in the signal power and spiking rate, which compromise the propagation and processing of information between neurons. We propose a transfer function to model the weakening effects on the AP. Our results show that demyelination induced by a cytokine storm not only degrades the signal but also impairs its propagation within the axon. Our proposed in silico model can analyse virus-induced neurodegeneration and enhance our understanding of virus-induced demyelination.

Temporal interference (TI) stimulation is a popular non-invasive neurostimulation technique that utilizes the following salient neural behavior: pure sinusoid (generated in off-target brain regions) appears to cause no stimulation, whereas modulated sinusoid (generated in target brain regions) does. To understand its effects and mechanisms, we examine responses of different cell types, excitatory pyramidal (Pyr) and inhibitory parvalbumin-expressing (PV) neurons, to pure and modulated sinusoids, in intact network as well as in isolation. In intact network, we present data showing that PV neurons are much less likely than Pyr neurons to exhibit TI stimulation. Remarkably, in isolation, our data shows that almost all Pyr neurons stop exhibiting TI stimulation. We conclude that TI stimulation is largely a network phenomenon. Indeed, PV neurons actively inhibit Pyr neurons in the off-target regions due to pure sinusoids (in off-target regions) generating much higher PV firing rates than modulated sinusoids in the target regions. Additionally, we use computational studies to support and extend our experimental observations.