Hierarchical excitatory synaptic connectivity in mouse olfactory cortex

Embryonically active piriform cortex neurons promote intracortical recurrent connectivity during development

Neuronal activity plays a critical role in the maturation of circuits that propagate sensory information into the brain. How widely does early activity regulate circuit maturation across the developing brain? Here, we used targeted recombination in active populations (TRAP) to perform a brain-wide survey for prenatally active neurons in mice and identified the piriform cortex as an abundantly TRAPed region. Whole-cell recordings in neonatal slices revealed preferential interconnectivity within embryonically TRAPed piriform neurons and their enhanced synaptic connectivity with other piriform neurons. In vivo Neuropixels recordings in neonates demonstrated that embryonically TRAPed piriform neurons exhibit broad functional connectivity within piriform and lead spontaneous synchronized population activity during a transient neonatal period, when recurrent connectivity is strengthening. Selectively activating or silencing these neurons in neonates enhanced or suppressed recurrent synaptic strength, respectively. Thus, embryonically TRAPed piriform neurons represent an interconnected hub-like population whose activity promotes recurrent connectivity in early development.

Embryonically Active Piriform Cortex Neurons Promote Intracortical Recurrent Connectivity during Development

Neuronal activity plays a critical role in the maturation of circuits that propagate sensory information into the brain. How widely does early activity regulate circuit maturation across the developing brain? Here, we used Targeted Recombination in Active Populations (TRAP) to perform a brain-wide survey for prenatally active neurons in mice and identified the piriform cortex as an abundantly TRAPed region. Whole-cell recordings in neonatal slices revealed preferential interconnectivity within embryonically TRAPed piriform neurons and their enhanced synaptic connectivity with other piriform neurons. In vivo Neuropixels recordings in neonates demonstrated that embryonically TRAPed piriform neurons exhibit broad functional connectivity within piriform and lead spontaneous synchronized population activity during a transient neonatal period, when recurrent connectivity is strengthening. Selectively activating or silencing of these neurons in neonates enhanced or suppressed recurrent synaptic strength, respectively. Thus, embryonically TRAPed piriform neurons represent an interconnected hub-like population whose activity promotes recurrent connectivity in early development.

Alterations in Piriform and Bulbar Activity/Excitability/Coupling Upon Amyloid-β Administration in vivo Related to Olfactory Dysfunction

BACKGROUND

Deficits in odor detection and discrimination are premature symptoms of Alzheimer's disease (AD) that correlate with pathological signs in the olfactory bulb (OB) and piriform cortex (PCx). Similar olfactory dysfunction has been characterized in AD transgenic mice that overproduce amyloid-β peptide (Aβ), which can be prevented by reducing Aβ levels by immunological and pharmacological means, suggesting that olfactory dysfunction depends on Aβ accumulation and Aβ-driven alterations in the OB and/or PCx, as well as on their activation. However, this possibility needs further exploration.

OBJECTIVE

To characterize the effects of Aβ on OB and PCx excitability/coupling and on olfaction.

METHODS

Aβ oligomerized solution (containing oligomers, monomers, and protofibrils) or its vehicle were intracerebroventricularlly injected two weeks before OB and PCx excitability and synchrony were evaluated through field recordings in vivo and in brain slices. Synaptic transmission from the OB to the PCx was also evaluated in slices. Olfaction was assessed through the habituation/dishabituation test.

RESULTS

Aβ did not affect lateral olfactory tract transmission into the PCx but reduced odor habituation and cross-habituation. This olfactory dysfunction was related to a reduction of PCx and OB network activity power in vivo. Moreover, the coherence between PCx-OB activities was also reduced by Aβ. Finally, Aβ treatment exacerbated the 4-aminopyridine-induced excitation in the PCx in slices.

CONCLUSION

Our results show that Aβ-induced olfactory dysfunction involves a complex set of pathological changes at different levels of the olfactory pathway including alterations in PCx excitability and its coupling with the OB. These pathological changes might contribute to hyposmia in AD.

Parallel pathways of seizure generalization

Generalized convulsive status epilepticus is a life-threatening emergency, because recurrent convulsions can cause death or injury. A common form of generalized convulsive status epilepticus is of focal onset. The neuronal circuits activated during seizure spread from the hippocampus, a frequent site of seizure origin, to the bilateral motor cortex, which mediates convulsive seizures, have not been delineated. Status epilepticus was initiated by electrical stimulation of the hippocampus. Neurons transiently activated during seizures were labelled with tdTomato and then imaged following brain slice clearing. Hippocampus was active throughout the episode of status epilepticus. Neuronal activation was observed in hippocampus parahippocampal structures: subiculum, entorhinal cortex and perirhinal cortex, septum, and olfactory system in the initial phase status epilepticus. The tdTomato-labelled neurons occupied larger volumes of the brain as seizures progressed and at the peak of status epilepticus, motor and somatosensory cortex, retrosplenial cortex, and insular cortex also contained tdTomato-labelled neurons. In addition, motor thalamic nuclei such as anterior and ventromedial, midline, reticular, and posterior thalamic nuclei were also activated. Furthermore, circuits proposed to be crucial for systems consolidation of memory: entorhinal cortex, retrosplenial cortex, cingulate gyrus, midline thalamic nuclei and prefrontal cortex were intensely active during periods of generalized tonic-clonic seizures. As the episode of status epilepticus waned, smaller volume of brain was activated. These studies suggested that seizure spread could have occurred via canonical thalamocortical pathway and many cortical structures involved in memory consolidation. These studies may help explain retrograde amnesia following seizures.

Optogenetic Mapping of Intracortical Circuits Originating from Semilunar Cells in the Piriform Cortex

Despite its comparatively simple trilaminar architecture, the primary olfactory (piriform) cortex of mammals is capable of performing sophisticated sensory processing, an ability that is thought to depend critically on its extensive associational (intracortical) excitatory circuits. Here, we used a novel transgenic mouse model and optogenetics to measure the connectivity of associational circuits that originate in semilunar (SL) cells in layer 2a of the anterior piriform cortex (aPC). We generated a mouse line (48L) in which channelrhodopsin-2 (ChR) could be selectively expressed in a subset of SL cells. Light-evoked excitatory postsynaptic currents (EPSCs) could be evoked in superficial pyramidal cells (17.4% of n = 86 neurons) and deep pyramidal cells (33.3%, n = 9) in the aPC, but never in ChR- SL cells (0%, n = 34). Thus, SL cells monosynaptically excite pyramidal cells, but not other SL cells. Light-evoked EPSCs were also selectively elicited in 3 classes of GABAergic interneurons in layer 3 of the aPC. Our results show that SL cells are specialized for providing feedforward excitation of specific classes of neurons in the aPC, confirming that SL cells comprise a functionally distinctive input layer.

The global landscape of cognition: hierarchical aggregation as an organizational principle of human cortical networks and functions

Though widely hypothesized, limited evidence exists that human brain functions organize in global gradients of abstraction starting from sensory cortical inputs. Hierarchical representation is accepted in computational networks, and tentatively in visual neuroscience, yet no direct holistic demonstrations exist in vivo. Our methods developed network models enriched with tiered directionality, by including input locations, a critical feature for localizing representation in networks generally. Grouped primary sensory cortices defined network inputs, displaying global connectivity to fused inputs. Depth-oriented networks guided analyses of fMRI databases (~17,000 experiments;~1/4 of fMRI literature). Formally, we tested whether network depth predicted localization of abstract versus concrete behaviors over the whole set of studied brain regions. For our results, new cortical graph metrics, termed network-depth, ranked all databased cognitive function activations by network-depth. Thus, we objectively sorted stratified landscapes of cognition, starting from grouped sensory inputs in parallel, progressing deeper into cortex. This exposed escalating amalgamation of function or abstraction with increasing network-depth, globally. Nearly 500 new participants confirmed our results. In conclusion, data-driven analyses defined a hierarchically ordered connectome, revealing a related continuum of cognitive function. Progressive functional abstraction over network depth may be a fundamental feature of brains, and is observed in artificial networks.

Emergence of Slow-Switching Assemblies in Structured Neuronal Networks

Unraveling the interplay between connectivity and spatio-temporal dynamics in neuronal networks is a key step to advance our understanding of neuronal information processing. Here we investigate how particular features of network connectivity underpin the propensity of neural networks to generate slow-switching assembly (SSA) dynamics, i.e., sustained epochs of increased firing within assemblies of neurons which transition slowly between different assemblies throughout the network. We show that the emergence of SSA activity is linked to spectral properties of the asymmetric synaptic weight matrix. In particular, the leading eigenvalues that dictate the slow dynamics exhibit a gap with respect to the bulk of the spectrum, and the associated Schur vectors exhibit a measure of block-localization on groups of neurons, thus resulting in coherent dynamical activity on those groups. Through simple rate models, we gain analytical understanding of the origin and importance of the spectral gap, and use these insights to develop new network topologies with alternative connectivity paradigms which also display SSA activity. Specifically, SSA dynamics involving excitatory and inhibitory neurons can be achieved by modifying the connectivity patterns between both types of neurons. We also show that SSA activity can occur at multiple timescales reflecting a hierarchy in the connectivity, and demonstrate the emergence of SSA in small-world like networks. Our work provides a step towards understanding how network structure (uncovered through advancements in neuroanatomy and connectomics) can impact on spatio-temporal neural activity and constrain the resulting dynamics.

Revealing cell assemblies at multiple levels of granularity

BACKGROUND

Current neuronal monitoring techniques, such as calcium imaging and multi-electrode arrays, enable recordings of spiking activity from hundreds of neurons simultaneously. Of primary importance in systems neuroscience is the identification of cell assemblies: groups of neurons that cooperate in some form within the recorded population.

NEW METHOD

We introduce a simple, integrated framework for the detection of cell-assemblies from spiking data without a priori assumptions about the size or number of groups present. We define a biophysically-inspired measure to extract a directed functional connectivity matrix between both excitatory and inhibitory neurons based on their spiking history. The resulting network representation is analyzed using the Markov Stability framework, a graph theoretical method for community detection across scales, to reveal groups of neurons that are significantly related in the recorded time-series at different levels of granularity.

RESULTS AND COMPARISON WITH EXISTING METHODS

Using synthetic spike-trains, including simulated data from leaky-integrate-and-fire networks, our method is able to identify important patterns in the data such as hierarchical structure that are missed by other standard methods. We further apply the method to experimental data from retinal ganglion cells of mouse and salamander, in which we identify cell-groups that correspond to known functional types, and to hippocampal recordings from rats exploring a linear track, where we detect place cells with high fidelity.

CONCLUSIONS

We present a versatile method to detect neural assemblies in spiking data applicable across a spectrum of relevant scales that contributes to understanding spatio-temporal information gathered from systems neuroscience experiments.