Excitatory Connections Research Articles

Data-Driven Models of Efficient Chromatic Coding in the Outer Retina.

Recent experimental work on zebrafish has shown the in vivo activity of photoreceptors and horizontal cells (HCs) as a function of the stimulus spectrum, highlighting the appearance of chromatic-opponent signals at their first synaptic connection. Altogether with the observed lack of excitatory intercone connections, these findings suggest that the mechanism yielding early color opponency in zebrafish is dominated by inhibitory feedback. We propose a neuronal population model based on zebrafish retinal circuitry to investigate whether networks with predominantly inhibitory feedback are more advantageous in encoding chromatic information than networks with mixed excitatory and inhibitory mechanisms. We show that networks with dominant inhibitory feedback exhibit a unique and reliable encoding of chromatic information. In contrast, this property is not guaranteed in networks with strong excitatory intercone connections, exhibiting bistability. These findings provide a theoretical explanation for the absence of excitatory intercone couplings in zebrafish color circuits. In addition, our study shows that these networks, with only one type of horizontal cell, are suitable to encode most of the variance from the zebrafish environment. However, at least two successive layers of inhibitory neurons are needed to reach the optimum. Finally, we contrast the encoding performance of networks with different opsin sensitivities, showing an improvement of only 13% compared with zebrafish, suggesting that the zebrafish retina is adapted to encode color information from its habitat efficiently.

Predictable Fluctuations in Excitatory Synaptic Strength Due to Natural Variation in Presynaptic Firing Rate.

Many controlled in vitro studies have demonstrated how postsynaptic responses to presynaptic spikes are not constant but depend on short-term synaptic plasticity (STP) and the detailed timing of presynaptic spikes. However, the effects of short-term plasticity (depression and facilitation) are not limited to short, subsecond timescales. The effects of STP appear on long timescales as changes in presynaptic firing rates lead to changes in steady-state synaptic transmission. Here, we examine the relationship between natural variations in the presynaptic firing rates and spike transmission in vivo Using large-scale spike recordings in awake male and female mice from the Allen Institute Neuropixels dataset, we first detect putative excitatory synaptic connections based on cross-correlations between the spike trains of millions of pairs of neurons. For the subset of pairs where a transient, excitatory effect was detected, we use a model-based approach to track fluctuations in synaptic efficacy and find that efficacy varies substantially on slow (∼1 min) timescales over the course of these recordings. For many connections, the efficacy fluctuations are correlated with fluctuations in the presynaptic firing rate. To understand the potential mechanisms underlying this relationship, we then model the detailed probability of postsynaptic spiking on a millisecond timescale, including both slow changes in postsynaptic excitability and monosynaptic inputs with short-term plasticity. The detailed model reproduces the slow efficacy fluctuations observed with many putative excitatory connections, suggesting that these fluctuations can be both directly predicted based on the time-varying presynaptic firing rate and, at least partly, explained by the cumulative effects of STP.SIGNIFICANCE STATEMENT The firing rates of individual neurons naturally vary because of stimuli, movement, and brain state. Models of synaptic transmission predict that these variations in firing rates should be accompanied by slow fluctuations in synaptic strength because of short-term depression and facilitation. Here, we characterize the magnitude and predictability of fluctuations in synaptic strength in vivo using large-scale spike recordings. For putative excitatory connections from a wide range of brain areas, we find that typical synaptic efficacy varies as much as ∼70%, and in many cases the fluctuations are well described by models of short-term synaptic plasticity. These results highlight the dynamic nature of in vivo synaptic transmission and the interplay between synaptic strength and firing rates in awake animals.

Dose-response relationship between the variables of unilateral optogenetic stimulation and transcallosal evoked responses in rat motor cortex.

Efficient interhemispheric integration of neural activity between left and right primary motor cortex (M1) is critical for inter-limb motor control. We employed optogenetic stimulation to establish a framework for probing transcallosal M1–M1 interactions in rats. We performed optogenetic stimulation of excitatory neurons in right M1 of male Sprague-Dawley rats. We recorded the transcallosal evoked potential in contralateral left M1 via chronically implanted electrodes. Recordings were performed under anesthesia combination of dexmedetomidine and a low concentration of isoflurane. We systematically varied the stimulation intensity and duration to characterize the relationship between stimulation parameters in right M1 and the characteristics of the evoked intracortical potentials in left M1. Optogenetic stimulation of right M1 consistently evoked a transcallosal response in left M1 with a consistent negative peak (N1) that sometimes was preceded by a smaller positive peak (P1). Higher stimulation intensity or longer stimulation duration gradually increased N1 amplitude and reduced N1 variability across trials. A combination of stimulation intensities of 5–10 mW with stimulus durations of 1–10 ms were generally sufficient to elicit a robust transcallosal response in most animal, with our optic fiber setup. Optogenetically stimulated excitatory neurons in M1 can reliably evoke a transcallosal response in anesthetized rats. Characterizing the relationship between “stimulation dose” and “response magnitude” (i.e., the gain function) of transcallosal M1-to-M1 excitatory connections can be used to optimize the variables of optogenetic stimulation and ensure stimulation efficacy.

Repeated stress exposure leads to structural synaptic instability prior to disorganization of hippocampal coding and impairments in learning

Stress exposure impairs brain structure and function, resulting in cognitive deficits and increased risk for psychiatric disorders such as depression, schizophrenia, anxiety and post-traumatic stress disorder. In particular, stress exposure affects function and structure of hippocampal CA1 leading to impairments in episodic memory. Here, we applied longitudinal deep-brain optical imaging to investigate the link between changes in activity patterns and structural plasticity of dorsal CA1 pyramidal neurons and hippocampal-dependent learning and memory in mice exposed to stress. We found that several days of repeated stress led to a substantial increase in neuronal activity followed by disruption of the temporal structure of this activity and spatial coding. We then tracked dynamics of structural excitatory connectivity as a potential underlying cause of the changes in activity induced by repeated stress. We thus discovered that exposure to repeated stress leads to an immediate decrease in spinogenesis followed by decrease in spine stability. By comparison, acute stress led to stabilization of the spines born in temporal proximity to the stressful event. Importantly, the temporal relationship between changes in activity levels, structural connectivity and activity patterns, suggests that loss of structural connectivity mediates the transition between increased activity and impairment of temporal organization and spatial information content in dorsal CA1 upon repeated stress exposure.

Early impairment of cortical circuit plasticity and connectivity in the 5XFAD Alzheimer’s disease mouse model

Genetic risk factors for neurodegenerative disorders, such as Alzheimer’s disease (AD), are expressed throughout the life span. How these risk factors affect early brain development and function remain largely unclear. Analysis of animal models with high constructive validity for AD, such as the 5xFAD mouse model, may provide insights on potential early neurodevelopmental effects that impinge on adult brain function and age-dependent degeneration. The 5XFAD mouse model over-expresses human amyloid precursor protein (APP) and presenilin 1 (PS1) harboring five familial AD mutations. It is unclear how the expression of these mutant proteins affects early developing brain circuits. We found that the prefrontal cortex (PFC) layer 5 (L5) neurons in 5XFAD mice exhibit transgenic APP overloading at an early post-weaning age. Impaired synaptic plasticity (long-term potentiation, LTP) was seen at 6–8 weeks age in L5 PFC circuit, which was correlated with increased intracellular APP. APP overloading was also seen in L5 pyramidal neurons in the primary visual cortex (V1) during the critical period of plasticity (4–5 weeks age). Whole-cell patch clamp recording in V1 brain slices revealed reduced intrinsic excitability of L5 neurons in 5XFAD mice, along with decreased spontaneous miniature excitatory and inhibitory inputs. Functional circuit mapping using laser scanning photostimulation (LSPS) combined with glutamate uncaging uncovered reduced excitatory synaptic connectivity onto L5 neurons in V1, and a more pronounced reduction in inhibitory connectivity, indicative of altered excitation and inhibition during VC critical period. Lastly, in vivo single-unit recording in V1 confirmed that monocular visual deprivation-induced ocular dominance plasticity during critical period was impaired in 5XFAD mice. Our study reveals plasticity deficits across multiple cortical regions and indicates altered early cortical circuit developmental trajectory as a result of mutant APP/PS1 over-expression.

Loss of oligodendrocyte ErbB receptor signaling leads to hypomyelination, reduced density of parvalbumin-expressing interneurons, and inhibitory function in the auditory cortex.

For a long time, myelin was thought to be restricted to excitatory neurons, and studies on dysmyelination focused primarily on excitatory cells. Recent evidence showed that axons of inhibitory neurons in the neocortex are also myelinated, but the role of myelin on inhibitory circuits remains unknown. Here we studied the impact of mild hypomyelination on both excitatory and inhibitory connectivity in the primary auditory cortex (A1) with well-characterized mouse models of hypomyelination due to loss of oligodendrocyte ErbB receptor signaling. Using laser-scanning photostimulation, we found that mice with mild hypomyelination have reduced functional inhibitory connections to A1 L2/3 neurons without changes in excitatory connections, resulting in altered excitatory/inhibitory balance. These effects are not associated with altered expression of GABAergic and glutamatergic synaptic components, but with reduced density of parvalbumin-positive (PV+ ) neurons, axons, and synaptic terminals, which reflect reduced PV expression by interneurons rather than PV+ neuronal loss. While immunostaining shows that hypomyelination occurs in both PV+ and PV- axons, there is a strong correlation between MBP and PV expression, suggesting that myelination influences PV expression. Together, the results indicate that mild hypomyelination impacts A1 neuronal networks, reducing inhibitory activity, and shifting networks towards excitation.

Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex.

Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.

Unmasking Schizophrenia: Synaptic Pruning in Adolescence Reveals a Latent Physiological Vulnerability in Prefrontal Recurrent Networks

Theories of the pathophysiology in schizophrenia are converging on the synapse. This special issue of Biological Psychiatry collects papers from leading researchers that suggest a hypothesis that multiple factors spanning many levels lead to synaptic dysfunction in recurrent circuits in the prefrontal cortex (PFC). The hypothesis (Figure 1) suggests that the defect within the PFC is established during early development but remains latent through childhood. Pruning of excitatory synapses during adolescence, resulting in lower synaptic density in persons with schizophrenia, triggers the emergence of symptoms. The lower synaptic density results in deficits in cognitive processes, including working memory, because overpruned neural circuits cannot support the relevant computations ( 1 Averbeck B.B. Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning. Proc Natl Acad Sci U S A. 2022; 119e2121331119 Crossref Scopus (0) Google Scholar ). Additionally, excessive prefrontal pruning leads to striatal hyperdopaminergia through increased activation of midbrain dopamine neurons by prefrontal input. The decreased synaptic density following adolescent pruning could be due to genetic or epigenetic effects that lead to an inability to build stable synapses or excessive pruning of established synapses. The excessive pruning could follow from overactive pruning mechanisms or from decreased excitatory synaptic activity due to synaptic changes local to the PFC or prolonged decreases in thalamic input across development. All of these factors may converge to alter spike timing dynamics in prefrontal recurrent circuits in adolescence, reducing synchronous neural activity and accelerating synaptic disconnection via activity-dependent mechanisms ( 2 Zick J.L. Crowe D.A. Blackman R.K. Schultz K. Bergstrand D.W. DeNicola A.L. et al. Disparate insults relevant to schizophrenia converge on impaired spike synchrony and weaker synaptic interactions in prefrontal local circuits. Curr Biol. 2022; 32: 14-25.e4 Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar ). Further, synaptic pruning is mediated by components of the immune system, and in utero immune challenge may affect adolescent pruning. Decreased synaptic activity can also lead to increased pruning as pruning removes weak synapses. Thus, multiple effects converging on the synapse could lead to a PFC with fewer excitatory synaptic connections, and this decreased recurrent connectivity could lead to cognitive deficits and increased striatal dopamine and psychosis.

Temporal filters in response to presynaptic spike trains: interplay of cellular, synaptic and short-term plasticity time scales.

Temporal filters, the ability of postsynaptic neurons to preferentially select certain presynaptic input patterns over others, have been shown to be associated with the notion of information filtering and coding of sensory inputs. Short-term plasticity (depression and facilitation; STP) has been proposed to be an important player in the generation of temporal filters. We carry out a systematic modeling, analysis and computational study to understand how characteristic postsynaptic (low-, high- and band-pass) temporal filters are generated in response to periodic presynaptic spike trains in the presence STP. We investigate how the dynamic properties of these filters depend on the interplay of a hierarchy of processes, including the arrival of the presynaptic spikes, the activation of STP, its effect on the excitatory synaptic connection efficacy, and the response of the postsynaptic cell. These mechanisms involve the interplay of a collection of time scales that operate at the single-event level (roughly, during each presynaptic interspike-interval) and control the long-term development of the temporal filters over multiple presynaptic events. These time scales are generated at the levels of the presynaptic cell (captured by the presynaptic interspike-intervals), short-term depression and facilitation, synaptic dynamics and the post-synaptic cellular currents. We develop mathematical tools to link the single-event time scales with the time scales governing the long-term dynamics of the resulting temporal filters for a relatively simple model where depression and facilitation interact at the level of the synaptic efficacy change. We extend our results and tools to account for more complex models. These include multiple STP time scales and non-periodic presynaptic inputs. The results and ideas we develop have implications for the understanding of the generation of temporal filters in complex networks for which the simple feedforward network we investigate here is a building block.

Electrophysiological Validation of Monosynaptic Connectivity between Premotor Interneurons and the aCC Motoneuron in the Drosophila Larval CNS.

The Drosophila connectome project aims to map the synaptic connectivity of entire larval and adult fly neural networks, which is essential for understanding nervous system development and function. So far, the project has produced an impressive amount of electron microscopy data that has facilitated reconstructions of specific synapses, including many in the larval locomotor circuit. While this breakthrough represents a technical tour de force, the data remain underutilized, partly because of a lack of functional validation of reconstructions. Attempts to validate connectivity posited by the connectome project, have mostly relied on behavioral assays and/or GFP reconstitution across synaptic partners (GRASP) or GCaMP imaging. While these techniques are useful, they have limited spatial or temporal resolution. Electrophysiological assays of synaptic connectivity overcome these limitations. Here, we combine patch-clamp recordings with optogenetic stimulation in male and female larvae, to test synaptic connectivity proposed by connectome reconstructions. Specifically, we use multiple driver lines to confirm that several connections between premotor interneurons and the anterior corner cell motoneuron are, as the connectome project suggests, monosynaptic. In contrast, our results also show that conclusions based on GRASP imaging may provide false-positive results regarding connectivity between cells. We also present a novel imaging tool, based on the same technology as our electrophysiology, as a favorable alternative to GRASP imaging. Finally, of eight Gal4 lines tested, five are reliably expressed in the premotor interneurons they are targeted to. Thus, our work highlights the need to confirm functional synaptic connectivity, driver line specificity, and use of appropriate genetic tools to support connectome projects.SIGNIFICANCE STATEMENT The Drosophila connectome project aims to provide a complete description of connectivity between neurons in an organism that presents experimental advantages over other models. It has reconstructed hundreds of thousands of synaptic connections of the fly larva by manual identification of anatomic landmarks present in serial section transmission electron microscopy (ssTEM) volumes of the larval CNS. We use a highly reliable electrophysiological approach to verify these connections, providing useful insight into the accuracy of work based on ssTEM. We also present a novel imaging tool for validating excitatory monosynaptic connections between cells and show that several genetic driver lines designed to target neurons of the larval connectome exhibit nonspecific and/or unreliable expression.

Long-Duration Sound-Induced Facilitation Changes Population Activity in the Inferior Colliculus.

The inferior colliculus (IC) is at the midpoint of the auditory system and integrates virtually all information ascending from the auditory brainstem, organizes it, and transmits the results to the auditory forebrain. Its abundant, excitatory local connections are crucial for this task. This study describes a long duration sound (LDS)-induced potentiation in the IC that changes both subsequent tone-evoked responses and spontaneous activity. Afterdischarges, changes of spontaneous spiking following an LDS, were seen previously in single neurons. Here, we used multi-channel probes to record activity before and after a single, tetanic sound and describe the changes in a population of IC neurons. Following a 60 s narrowband-noise stimulation, a subset of recording channels (∼16%) showed afterdischarges. A facilitated response spike rate to tone pips following an LDS was also observed in ∼16% of channels. Both channels with an afterdischarge and channels with facilitated tone responses had higher firing rates in response to LDS, and the magnitude of the afterdischarges increased with increased responses to the LDS. This is the first study examining the effect of LDS stimulation on tone-evoked responses. This observed facilitation in vivo has similarities to post-tetanic potentiation in vitro as both manner of induction (strong stimulation for several seconds) as well as time-course of the facilitation (second to minute range) are comparable. Channels with and without facilitation appear to be intermixed and distributed widely in the central nucleus of IC, and this suggests a heretofore unknown property of some IC neurons or their circuits. Consequently, this sound-evoked facilitation may enhance the sound-evoked output of these neurons, while, simultaneously, most other IC neurons have reduced or unchanged output in response to the same stimulus.

Edge-colored directed subgraph enumeration on the connectome

Following significant advances in image acquisition, synapse detection, and neuronal segmentation in connectomics, researchers have extracted an increasingly diverse set of wiring diagrams from brain tissue. Neuroscientists frequently represent these wiring diagrams as graphs with nodes corresponding to a single neuron and edges indicating synaptic connectivity. The edges can contain “colors” or “labels”, indicating excitatory versus inhibitory connections, among other things. By representing the wiring diagram as a graph, we can begin to identify motifs, the frequently occurring subgraphs that correspond to specific biological functions. Most analyses on these wiring diagrams have focused on hypothesized motifs—those we expect to find. However, one of the goals of connectomics is to identify biologically-significant motifs that we did not previously hypothesize. To identify these structures, we need large-scale subgraph enumeration to find the frequencies of all unique motifs. Exact subgraph enumeration is a computationally expensive task, particularly in the edge-dense wiring diagrams. Furthermore, most existing methods do not differentiate between types of edges which can significantly affect the function of a motif. We propose a parallel, general-purpose subgraph enumeration strategy to count motifs in the connectome. Next, we introduce a divide-and-conquer community-based subgraph enumeration strategy that allows for enumeration per brain region. Lastly, we allow for differentiation of edges by types to better reflect the underlying biological properties of the graph. We demonstrate our results on eleven connectomes and publish for future analyses extensive overviews for the 26 trillion subgraphs enumerated that required approximately 9.25 years of computation time.

Connectivity and synaptic features of hilar mossy cells and their effects on granule cell activity along the hippocampal longitudinal axis.

The hippocampus is an elongated brain structure which runs along a ventral-to-dorsal axis in rodents, corresponding to the anterior-to-posterior axis in humans. A glutamatergic cell type in the dentate gyrus (DG), the mossy cells (MCs), establishes extensive excitatory collateral connections with the DG principal cells, the granule cells (GCs), and inhibitory interneurons in both hippocampal hemispheres along the longitudinal axis. Although coupling of two physically separated GC populations via long-axis projecting MCs is instrumental for information processing, the connectivity and synaptic features of MCs along the longitudinal axis are poorly defined. Here, using channelrhodopsin-2 assisted circuit mapping, we showed that MC excitation results in a low synaptic excitation-inhibition (E/I) balance in the intralamellar (local) GCs, but a high synaptic E/I balance in the translamellar (distant) ones. In agreement with the differential E/I balance along the ventrodorsal axis, activation of MCs either enhances or suppresses the local GC response to the cortical input, but primarily promotes the distant GC activation. Moreover, activation of MCs enhances the spike timing precision of the local GCs, but not that of the distant ones. Collectively, these findings suggest that MCs differentially regulate the local and distant GC activity through distinct synaptic mechanisms. KEY POINTS: Hippocampal mossy cell (MC) pathways differentially regulate granule cell (GC) activity along the longitudinal axis. MCs mediate a low excitation-inhibition balance in intralamellar (local) GCs, but a high excitation-inhibition balance in translamellar (distant) GCs. MCs enhance the spiking precision of local GCs, but not distant GCs. MCs either promote or suppress local GC activity, but primarily promote distant GC activation.

Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation

Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.

Local targets of T-stellate cells in the ventral cochlear nucleus.

T‐stellate cells in the ventral cochlear nucleus (VCN) are known to have local axon collaterals that terminate in the vicinity of their dendrites and cell bodies within the same isofrequency lamina in parallel with the auditory nerve fibers that innervate them. Excitatory synaptic connections between stellate cells within an isofrequency lamina are hypothesized to be involved in the nitric oxide‐mediated upregulation of T‐stellate responses to their auditory input. This could serve as a mechanism of variable gain control in the enhancement of responses to vowel spectral peaks. Previous studies have provided indirect evidence for these possible synaptic interconnections between T‐stellate cells, but unequivocal identification has yet to be established. Here, we used retrograde neuronal tracing with adeno‐associated viral vector or biotinylated dextran amine injected into the inferior colliculus (IC) to detect the postsynaptic target of T‐stellate cells within the VCN. We show that backfilled T‐stellate cell axons make monosynapatic connections on the labeled cell bodies and dendrites of other labeled T‐stellate cells within an isofrequency lamina. Electron microscopy revealed that T‐stellate terminals can also make synapses on structures not retrogradely labeled from the IC. Glycine antibodies combined with the viral labeling indicated that these nonbackfilled structures that the labeled T‐stellate terminals were synapsing on are most likely the cell bodies and dendrites of two size categories of glycinergic VCN cells, whose sizes and relative numbers indicated they are the D‐ and L‐stellate cells. These cells are known to provide inhibitory inputs back onto T‐stellate cells. Our data indicate that, in addition to their auditory nerve input, T‐stellate cells provide a second modulatable excitatory input to both inhibitory and excitatory cells in a VCN isofrequency lamina and may play a significant role in acoustic information processing.

Relating a Spiking Neural Network Model and the Diffusion Model of Decision-Making.

Many models of decision making assume accumulation of evidence to threshold as a core mechanism to predict response probabilities and response times. A spiking neural network model (Wang, 2002) instantiates these mechanisms at the level of biophysically-plausible pools of neurons with excitatory and inhibitory connections, and has numerous model parameters tuned by physiological measures. The diffusion model (Ratcliff, 1978) is a cognitive model that can be fitted to a range of behaviors and conditions. We investigated how parameters of the cognitive-level diffusion model relate to the parameters of a neural-level spiking model. In each simulated "experiment", we generated "data" from the spiking neural network by factorially combining a manipulation of choice difficulty (via the input to the spiking model) and a manipulation of one of the core parameters of the spiking model. We then fitted the diffusion model to these simulated data to observe how manipulation of each core spiking model parameter mapped on to fitted drift rate, response threshold, and non-decision time. Manipulations of parameters in the spiking model related to input sensitivity, threshold, and stimulus processing time mapped on to their conceptual analogues in the diffusion model, namely drift rate, threshold, and non-decision time. Manipulations of parameters in the spiking model with no direct analogue to the diffusion model, non-stimulus-specific background input, strength of recurrent excitation, and receptor conductances, mapped on to threshold in the diffusion model. We discuss implications of these results for interpretations of fits of the diffusion model to behavioral data.

Internally generated population activity in cortical networks hinders information transmission.

How neuronal variability affects sensory coding is a central question in systems neuroscience, often with complex and model-dependent answers. Many studies explore population models with a parametric structure for response tuning and variability, preventing an analysis of how synaptic circuitry establishes neural codes. We study stimulus coding in networks of spiking neuron models with spatially ordered excitatory and inhibitory connectivity. The wiring structure is capable of producing rich population-wide shared neuronal variability that agrees with many features of recorded cortical activity. While both the spatial scales of feedforward and recurrent projections strongly affect noise correlations, only recurrent projections, and in particular inhibitory projections, can introduce correlations that limit the stimulus information available to a decoder. Using a spatial neural field model, we relate the recurrent circuit conditions for information limiting noise correlations to how recurrent excitation and inhibition can form spatiotemporal patterns of population-wide activity.

Complex regimes in electronic neuron-like oscillators with sigmoid coupling

The new version of electronic implementation of FitzHugh–Nagumo neuron model was proposed together with a new circuit for synapse (sigmoid activation function). The proposed neuron and synapse models provide better representation of activation function in biological neurons including possibility to model excitatory and inhibitory connections. Various regimes in two FitzHugh–Nagumo neurons were studied numerically and in hardware experiment. Different scenarios of oscillation emergence were investigated, including saddle-node cycle bifurcation leading to appearance of highly nonlinear limit cycles of large amplitude. Long living transients near these bifurcations were found those are of particular interest for modeling some metastable phenomena in living systems like sleep and epilepsy.

Translaminar recurrence from layer 5 suppresses superficial cortical layers

Information flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.

Biochemical Mechanisms that Control the Effects of RhoA Small GTPase Signaling on Synaptic Stability and Cognition

Dendritic spines are the site of most excitatory connections in the brain. Small GTPases act as binary switches that link cell surface receptors to persistent modifications in the morphogenesis of dendritic spines. Small GTPases are active when bound to GTP and inactive when GDP bound. The direct activation of small GTPases is accomplished by guanine nucleotide exchange factors (GEFs). The small GTPase RhoA, is enriched in dendritic spines and its activation can destabilize the actin cytoskeleton within spines reducing dendritic spine stability. Rodent studies suggest that excessive RhoA signaling causes cognitive impairment in part via its ability to reduce dendritic spine density in forebrain neurons. Despite the broad therapeutic potential of targeting the RhoA pathway as a means of enhancing cognition, the specific biochemical mechanisms that control its activity in neurons remain largely unknown. PDZ‐RhoGEF is a RhoA‐specific guanine nucleotide exchange factor that shows an unusually potent ability to activate RhoA. We show that PDZ‐RhoGEF destabilizes dendritic spines in cortical neurons and causes cortical‐dependent cognitive impairment. Ongoing studies are extending this analysis to determine if PDZ‐RhoGEF is similarly important for activity‐mediated remodeling of dendritic spines after NMDA receptor activation. Despite the importance of PDZ‐RhoGEF to synaptic and cognitive phenotypes, owing to a lack of studies, minimal is known about the biochemical mechanisms that regulate PDZ‐RhoGEF. Our recent findings indicate that PDZ‐RhoGEF activity and cellular localization is controlled by its interaction with the DISC1 scaffolding‐like protein, such that DISC1 helps localize PDZ‐RhoGEF to cellular membranes yet inhibits PDZ‐RhoGEF’s ability to activate RhoA. Experiments utilizing structured illumination microscopy are being conducted to further assess the functional consequences of the interaction between PDZ‐RhoGEF and DISC1 in neurons, and in particular, within dendritic spines. We theorize that the knockdown of DISC1 in neurons will result in the improper synaptic localization of PDZ‐RhoGEF with a concomitant increase in PDZ‐RhoGEF‐mediated RhoA activity. Collectively, these findings identify PDZ‐RhoGEF as a potent regulator of synaptic stability and cognition and highlight a previously unrecognized involvement for DISC1 in controlling RhoA activity via PDZ‐RhoGEF.