Propagation Of Neural Activity Research Articles

Regulation of spike propagation in feedforward neural networks through short-term synaptic plasticity

Both factors, multilayer Feedforward Neural Networks (FFNs) and short-term synaptic plasticity (STP), are considered crucial in the transmission and processing of neural signals. In this study, a 10-layer FFN was constructed to study the impact of STP on neuronal activity propagation. Neurons within the same layer do not have direct connections; instead, neurons between adjacent layers are randomly connected with a specific probability. The findings indicate that synaptic plasticity can regulate the network’s firing rate, synchronization, and output firing rate gain. Notably, short-term facilitation (STF) allows the network to exhibit high-pass filtering, while short-term depression (STD) achieves low-pass filtering. Combining STF and STD synapses in the FFN broadens the range of input firing rates effectively transmitted by the network. Increasing the proportion of STD-dominated synapses enhances the gain of low firing rate signals but reduces the gain of high firing rate signals. Adjusting the mix of synapses enables the network to implement bandpass filtering and control firing rate gain. These results underscore the effectiveness of modulating short-term synaptic plasticity in regulating neural activity propagation in FFNs.

Functional Dissection of Ipsilateral and Contralateral Neural Activity Propagation Using Voltage-Sensitive Dye Imaging in Mouse Prefrontal Cortex.

Prefrontal cortex (PFC) intrahemispheric activity and the interhemispheric connection have a significant impact on neuropsychiatric disorder pathology. This study aimed to generate a functional map of FC intrahemispheric and interhemispheric connections. Functional dissection of mouse PFCs was performed using the voltage-sensitive dye (VSD) imaging method with high speed (1 ms/frame), high resolution (256 × 256 pixels), and a large field of view (∼10 mm). Acute serial 350 μm slices were prepared from the bregma covering the PFC and numbered 1-5 based on their distance from the bregma (i.e., 1.70, 1.34, 0.98, 0.62, and 0.26 mm) with reference to the Mouse Brain Atlas (Paxinos and Franklin, 2008). The neural response to electrical stimulation was measured at nine sites and then averaged, and a functional map of the propagation patterns was created. Intracortical propagation was observed in slices 3-5, encompassing the anterior cingulate cortex (ACC) and corpus callosum (CC). The activity reached area 33 of the ACC. Direct white matter stimulation activated area 33 in both hemispheres. Similar findings were obtained via DiI staining of the CC. Imaging analysis revealed directional biases in neural signals traveling within the ACC, whereby the signal transmission speed and probability varied based on the signal direction. Specifically, the spread of neural signals from cg2 to cg1 was stronger than that from cingulate cortex area 1(cg1) to cingulate cortex area 2(cg2), which has implications for interhemispheric functional connections. These findings highlight the importance of understanding the PFC functional anatomy in evaluating neuromodulators like serotonin and dopamine, as well as other factors related to neuropsychiatric diseases.

A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice.

Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that can form both structural and functional connections with an organotypic hippocampal slice (OHS) is assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicate that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells are significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays shows that the delivered Mag-Neurobot is functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.

Lexicality-Modulated Influence of Auditory Cortex on Subthalamic Nucleus During Motor Planning for Speech.

Speech requires successful information transfer within cortical-basal ganglia loop circuits to produce the desired acoustic output. For this reason, up to 90% of Parkinson's disease patients experience impairments of speech articulation. Deep brain stimulation (DBS) is highly effective in controlling the symptoms of Parkinson's disease, sometimes alongside speech improvement, but subthalamic nucleus (STN) DBS can also lead to decreases in semantic and phonological fluency. This paradox demands better understanding of the interactions between the cortical speech network and the STN, which can be investigated with intracranial EEG recordings collected during DBS implantation surgery. We analyzed the propagation of high-gamma activity between STN, superior temporal gyrus (STG), and ventral sensorimotor cortices during reading aloud via event-related causality, a method that estimates strengths and directionalities of neural activity propagation. We employed a newly developed bivariate smoothing model based on a two-dimensional moving average, which is optimal for reducing random noise while retaining a sharp step response, to ensure precise embedding of statistical significance in the time-frequency space. Sustained and reciprocal neural interactions between STN and ventral sensorimotor cortex were observed. Moreover, high-gamma activity propagated from the STG to the STN prior to speech onset. The strength of this influence was affected by the lexical status of the utterance, with increased activity propagation during word versus pseudoword reading. These unique data suggest a potential role for the STN in the feedforward control of speech.

Brain state limits propagation of neural signals in laminar cortical circuits

Our perception of the environment relies on the efficient propagation of neural signals across cortical networks. During the time course of a day, neural responses fluctuate dramatically as the state of the brain changes to possibly influence how electrical signals propagate across neural circuits. Despite the importance of this issue, how patterns of spiking activity propagate within neuronal circuits in different brain states remains unknown. Here, we used multielectrode laminar arrays to reveal that brain state strongly modulates the propagation of neural activity across the layers of early visual cortex (V1). We optogenetically induced synchronized state transitions within a group of neurons and examined how far electrical signals travel during wakefulness and rest. Although optogenetic stimulation elicits stronger neural responses during wakefulness relative to rest, signals propagate only weakly across the cortical column during wakefulness, and the extent of spread is inversely related to arousal level. In contrast, the light-induced population activity vigorously propagates throughout the entire cortical column during rest, even when neurons are in a desynchronized wake-like state prior to light stimulation. Mechanistically, the influence of global brain state on the propagation of spiking activity across laminar circuits can be explained by state-dependent changes in the coupling between neurons. Our results impose constraints on the conclusions of causal manipulation studies attempting to influence neural function and behavior, as well as on previous computational models of perception assuming robust signal propagation across cortical layers and areas.

Whole-brain dynamics differentiate among cisgender and transgender individuals.

How the brain represents gender identity is largely unknown, but some neural differences have recently been discovered. We used an intrinsic ignition framework to investigate whether there are gender differences in the propagation of neural activity across the whole‐brain and within resting‐state networks. Studying 29 trans men and 17 trans women with gender incongruence, 22 cis women, and 19 cis men, we computed the capability of a given brain area in space to propagate activity to other areas (mean‐ignition), and the variability across time for each brain area (node‐metastability). We found that both measurements differentiated all groups across the whole brain. At the network level, we found that compared to the other groups, cis men showed higher mean‐ignition of the dorsal attention network and node‐metastability of the dorsal and ventral attention, executive control, and temporal parietal networks. We also found higher mean‐ignition values in cis men than in cis women within the executive control network, but higher mean‐ignition in cis women than cis men and trans men for the default mode. Node‐metastability was higher in cis men than cis women in the somatomotor network, while both mean‐ignition and node‐metastability were higher for cis men than trans men in the limbic network. Finally, we computed correlations between these measurements and a body image satisfaction score. Trans men's dissatisfaction as well as cis men's and cis women's satisfaction toward their own body image were distinctively associated with specific networks in each group. Overall, the study of the whole‐brain network dynamical complexity discriminates gender identity groups, functional dynamic approaches could help disentangle the complex nature of the gender dimension in the brain.

Theta waves, neural spikes and seizures can propagate by ephaptic coupling in vivo

Electric field coupling has been shown to be responsible for non-synaptic neural activity propagation in hippocampal slices and cortical slices. Epileptiform and slow-wave sleep activity can propagate by electric field coupling without using synaptic connections at speeds of ~0.1 m/s in vitro. However, the characteristics of the events that can propagate using electric field coupling through a volume conductor in vivo have not been studied. Thus, we tested the hypothesis that various types of neural signals such as interictal spikes, theta waves and seizures could propagate in vivo across a transection in the hippocampus. We induced epileptiform activity in 4 rats under anesthesia by injecting 4-aminopyridine in the temporal region of the hippocampus, four recording electrodes were inserted along the longitudinal axis of the hippocampus. A transection was made between the electrodes to study the propagation of the neural activity. Although 54% of the interictal spikes could propagate through the cut, only those spikes with a high amplitude and short duration had a high probability to do so. 70% of seizure events could propagate through the cut but parameters distinguishing between propagating and non-propagating seizure events could not be identified. Theta activity was also observed to propagate at a mean speed of 0.16 ± 0.12 m/s in the characteristic range of propagation using electric field coupling through the transection. The electric field volume conduction mechanism was confirmed by showing that propagation was blocked by placing a dielectric layer within the cut. The speed of propagation was not affected by the transection thereby providing further evidence that various types of neural signals including activity in the theta range can propagate by electric field coupling in-vivo.

Persistence of hierarchical network organization and emergent topologies in models of functional connectivity

Functional networks provide a topological description of activity patterns in the brain, as they stem from the propagation of neural activity on the underlying anatomical or structural network of synaptic connections. This latter is well known to be organized in hierarchical and modular way. While it is assumed that structural networks shape their functional counterparts, it is also hypothesized that alterations of brain dynamics come with transformations of functional connectivity. In this computational study, we introduce a novel methodology to monitor the persistence and breakdown of hierarchical order in functional networks, generated from computational models of activity spreading on both synthetic and real structural connectomes. We show that hierarchical connectivity appears in functional networks in a persistent way if the dynamics is set to be in the quasi-critical regime associated with optimal processing capabilities and normal brain function, while it breaks down in other (supercritical) dynamical regimes, often associated with pathological conditions. Our results offer important clues for the study of optimal neurocomputing architectures and processes, which are capable of controlling patterns of activity and information flow. We conclude that functional connectivity patterns achieve optimal balance between local specialized processing (i.e. segregation) and global integration by inheriting the hierarchical organization of the underlying structural architecture.

Neural activity temporal pattern dictates long-range propagation targets

Brain possesses a complex spatiotemporal architecture for efficient information processing and computing. However, it remains unknown how neural signal propagates to its intended targets brain-wide. Using optogenetics and functional MRI, we arbitrarily initiated various discrete neural activity pulse trains with different temporal patterns and revealed their distinct long-range propagation targets within the well-defined, topographically organized somatosensory thalamo-cortical circuit. We further observed that such neural activity propagation over long range could modulate brain-wide sensory functions. Electrophysiological analysis indicated that distinct propagation pathways arose from system level neural adaptation and facilitation in response to the neural activity temporal characteristics. Together, our findings provide fundamental insights into the long-range information transfer and processing. They directly support that temporal coding underpins the whole brain functional architecture in presence of the vast and relatively static anatomical architecture.

Low-frequency stimulation enhances ensemble co-firing and dexterity after stroke

Electrical stimulation is a promising tool for modulating brain networks. However, it is unclear how stimulation interacts with neural patterns underlying behavior. Specifically, how might external stimulation that is not sensitive to the state of ongoing neural dynamics reliably augment neural processing and improve function? Here, we tested how low-frequency epidural alternating current stimulation (ACS) in non-human primates recovering from stroke interacted with task-related activity in perilesional cortex and affected grasping. We found that ACS increased co-firing within task-related ensembles and improved dexterity. Using a neural network model, we found that simulated ACS drove ensemble co-firing and enhanced propagation of neural activity through parts of the network with impaired connectivity, suggesting a mechanism to link increased co-firing to enhanced dexterity. Together, our results demonstrate that ACS restores neural processing in impaired networks and improves dexterity following stroke. More broadly, these results demonstrate approaches to optimize stimulation to target neural dynamics.

The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation.

Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.

Self-propagating, non-synaptic epileptiform activity recruits neurons by endogenous electric fields

It is well documented that synapses play a significant role in the transmission of information between neurons. However, in the absence of synaptic transmission, neural activity has been observed to continue to propagate. Previous studies have shown that propagation of epileptiform activity takes place in the absence of synaptic transmission and gap junctions and is outside the range of ionic diffusion and axonal conduction. Computer simulations indicate that electric field coupling could be responsible for the propagation of neural activity under pathological conditions such as epilepsy. Electric fields can modulate neuronal membrane voltage, but there is no experimental evidence suggesting that electric field coupling can mediate self-regenerating propagation of neural activity. Here we examine the role of electric field coupling by eliminating all forms of neural communications except electric field coupling with a cut through the neural tissue. We show that 4-AP induced activity generates an electric field capable of recruiting neurons on the distal side of the cut. Experiments also show that applied electric fields with amplitudes similar to endogenous values can induce propagating waves. Finally, we show that canceling the electrical field at a given point can block spontaneous propagation. The results from these in vitro electrophysiology experiments suggest that electric field coupling is a critical mechanism for non-synaptic neural propagation and therefore could contribute to the propagation of epileptic activity in the brain.

Abstract #110: Ephaptic coupling, a mechanism for spontaneous neural propagation in the brain

It is well documented that synapses play a significant role in the transmission of information between neurons in the brain. However, in the absence of synaptic transmission, neural activity has been observed to continue to propagate. Several experimental results have shown that propagation of epileptiform activity in rodent hippocampi propagates at a speed of ∼0.1 m/s. This observed activity in the 4-AP model propagates independently of synaptic transmission and gap junctions, and is outside the range of ionic diffusion and axonal conduction speeds. Compartment modeling of pyramidal neurons indicate that ephaptic coupling, or endogenous electric fields, could be responsible for this propagation of neural activity in pathological conditions such as epilepsy. Recent studies suggest electric fields can activate neighboring neurons, thereby generating a self-propagating wave. However, there is no experimental data suggesting ephaptic coupling is necessary and sufficient for spontaneous, self-regenerating propagation of neural activity. Using in vitro and in vivo electrophysiology in combination with imaging of trans-membrane voltages using genetically encoded voltage indicators, we test the hypothesis that ephaptic coupling is a critical mechanism for non-synaptic neural propagation. We have developed a novel extracellular electric field clamp capable of measuring the endogenous field and generate an "anti" field to block non-synaptic spontaneous propagation in the rodent hippocampus (Figure 1A). By blocking propagation, we are able to show that ephaptic coupling is a necessary mechanism for propagation of spontaneous activity. Finally, since electric fields propagate as volume conductors, we test if activity can propagate through a complete physical cut of the tissue, thereby eliminating all other forms of close cell-to-cell communication and showing that electric fields alone are sufficient to mediate non-synaptic propagation. Preliminary results suggest that spontaneous epileptiform activity propagates by triggering the activity on the other side across the cut with ephaptic coupling without changing the speed (Figure 1B). Our findings suggest that ephaptic coupling is necessary and sufficient to mediate non-synaptic neural propagation. Further investigation of this mechanism could explain how focal seizures appear to start abruptly and unpredictably, and how the rare micro-seizures of human partial epilepsy (seizure-like events that are not clinically detectable and are resistant to most common antiepileptic drugs) propagate through the hippocampus and cortex. Furthermore, endogenous electric fields could play an important role in brain function and could provide an explanation for unresolved mechanisms of deep brain stimulation or transcranial direct current stimulation (tDCS).

A Finite-Difference Solution for the EEG Forward Problem in Inhomogeneous Anisotropic Media.

Accurate source localization of electroencephalographic (EEG) signals requires detailed information about the geometry and physical properties of head tissues. Indeed, these strongly influence the propagation of neural activity from the brain to the sensors. Finite difference methods (FDMs) are head modelling approaches relying on volumetric data information, which can be directly obtained using magnetic resonance (MR) imaging. The specific goal of this study is to develop a computationally efficient FDM solution that can flexibly integrate voxel-wise conductivity and anisotropy information. Given the high computational complexity of FDMs, we pay particular attention to attain a very low numerical error, as evaluated using exact analytical solutions for spherical volume conductor models. We then demonstrate the computational efficiency of our FDM numerical solver, by comparing it with alternative solutions. Finally, we apply the developed head modelling tool to high-resolution MR images from a real experimental subject, to demonstrate the potential added value of incorporating detailed voxel-wise conductivity and anisotropy information. Our results clearly show that the developed FDM can contribute to a more precise head modelling, and therefore to a more reliable use of EEG as a brain imaging tool.

T104. Neural correlates of sign language and spoken language revealed by electrocorticography

Introduction Electrocorticography (ECoG) is a powerful tool to monitor cortical neurophysiology and can be employed to elucidate high order cognitive functions such as language. Clinically, electrical stimulation mapping (ESM) is the gold standard used to identify eloquent cortex which should be spared resection during surgery for patients. We developed a battery of tasks that mirror the ESM paradigm but can functionally track neural activity from stimulus presentation through speech output under multiple cognitive demands. Here we describe the neural propagation maps during both speech and sign language output in a case of a 28 year old male, hearing intact and bilingual in English and American sign language, with pharmaco-resistant epilepsy who was surgically implanted with electrodes for the clinical purpose of identifying his seizure onset zones. Methods The patient was implanted, for the purposes of his clinical care, with an electrode grid over the left temporal parietal occipital cortex, strips over the left frontal, temporal, and occipital regions, and depths within the left parietal lobe. During lulls in clinical treatment, we administered five language tasks involving visual naming, word reading, auditory repetition, auditory naming, and auditory comprehension. We focused our analyses on changes in high gamma activity (70–150 Hz) during the tasks, as high gamma activation has been previously shown to robustly track single trial cortical activity and correlates with neural population firing rates and fMRI BOLD responses. The patient also underwent electrical stimulation mapping using similar language tasks of visual naming, auditory naming, and auditory comprehension, as part of his clinical work up to identify eloquent cortex. Results We identified brain regions with high gamma activation during our language tasks in both spoken English and sign language. In addition we identified discrete regions in the frontal, temporal, parietal, and occipital cortices with sign language specific responses compared to spoken English and provide evidence for temporal propagation of neural activity from post-central to occipital cortices during sign language production. Conclusion We used ECoG high gamma activity to track neural dynamics of language processing in both spoken English and American sign language and to help map language cortex to assist in identifying eloquent regions during electrical brain stimulation.

Brain network dynamics in the human articulatory loop.

The articulatory loop is a fundamental component of language function, involved in the short-term buffer of auditory information followed by its vocal reproduction. We characterized the network dynamics of the human articulatory loop, using invasive recording and stimulation. We measured high-gamma activity70-110 Hz recorded intracranially when patients with epilepsy either only listened to, or listened to and then reproduced two successive tones by humming. We also conducted network analyses, and analyzed behavioral responses to cortical stimulation. Presentation of the initial tone elicited high-gamma augmentation bilaterally in the superior-temporal gyrus (STG) within 40ms, and in the precentral and inferior-frontal gyri (PCG and IFG) within 160ms after sound onset. During presentation of the second tone, high-gamma augmentation was reduced in STG but enhanced in IFG. The task requiring tone reproduction further enhanced high-gamma augmentation in PCG during and after sound presentation. Event-related causality (ERC) analysis revealed dominant flows within STG immediately after sound onset, followed by reciprocal interactions involving PCG and IFG. Measurement of cortico-cortical evoked-potentials (CCEPs) confirmed connectivity between distant high-gamma sites in the articulatory loop. High-frequency stimulation of precentral high-gamma sites in either hemisphere induced speech arrest, inability to control vocalization, or forced vocalization. Vocalization of tones was accompanied by high-gamma augmentation over larger extents of PCG. Bilateral PCG rapidly and directly receives feed-forward signals from STG, and may promptly initiate motor planning including sub-vocal rehearsal for short-term buffering of auditory stimuli. Enhanced high-gamma augmentation in IFG during presentation of the second tone may reflect high-order processing of the tone sequence. The articulatory loop employs sustained reciprocal propagation of neural activity across a network of cortical sites with strong neurophysiological connectivity.

Mapping Horizontal Spread of Activity in Monkey Motor Cortex Using Single Pulse Microstimulation

Anatomical studies have demonstrated that distant cortical points are interconnected through long range axon collaterals of pyramidal cells. However, the functional properties of these intrinsic synaptic connections, especially their relationship with the cortical representations of body movements, have not been systematically investigated. To address this issue, we used multielectrode arrays chronically implanted in the motor cortex of two rhesus monkeys to analyze the effects of single-pulse intracortical microstimulation (sICMS) applied at one electrode on the neuronal activities recorded at all other electrodes. The temporal and spatial distribution of the evoked responses of single and multiunit activities was quantified to determine the properties of horizontal propagation. The typical responses were characterized by a brief excitatory peak followed by inhibition of longer duration. Significant excitatory responses to sICMS could be evoked up to 4 mm away from the stimulation site, but the strength of the response decreased exponentially and its latency increased linearly with the distance. We then quantified the direction and strength of the propagation in relation to the somatotopic organization of the motor cortex. We observed that following sICMS the propagation of neural activity is mainly directed rostro-caudally near the central sulcus but follows medio-lateral direction at the most anterior electrodes. The fact that these interactions are not entirely symmetrical may characterize a critical functional property of the motor cortex for the control of upper limb movements. Overall, these results support the assumption that the motor cortex is not functionally homogeneous but forms a complex network of interacting subregions.

Dynamic range in the C. elegans brain network.

We study external electrical perturbations and their responses in the brain dynamic network of the Caenorhabditis elegans soil worm, given by the connectome of its large somatic nervous system. Our analysis is inspired by a realistic experiment where one stimulates externally specific parts of the brain and studies the persistent neural activity triggered in other cortical regions. In this work, we perturb groups of neurons that form communities, identified by the walktrap community detection method, by trains of stereotypical electrical Poissonian impulses and study the propagation of neural activity to other communities by measuring the corresponding dynamic ranges and Steven law exponents. We show that when one perturbs specific communities, keeping the rest unperturbed, the external stimulations are able to propagate to some of them but not to all. There are also perturbations that do not trigger any response. We found that this depends on the initially perturbed community. Finally, we relate our findings for the former cases with low neural synchronization, self-criticality, and large information flow capacity, and interpret them as the ability of the brain network to respond to external perturbations when it works at criticality and its information flow capacity becomes maximal.

A Frequency-Selective CMOS IC-Based Pulse Generator for Recording and Imaging in the Auditory Cortex In Vivo

A Frequency-Selective CMOS IC-Based Pulse Generator for Recording and Imaging in the Auditory Cortex In Vivo

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array