Graph analysis of the anatomical network organization of the hippocampal formation and parahippocampal region in the rat

Hunger, Satiety, and Their Vulnerabilities

The psychological states of hunger and satiety play an important role in regulating human food intake. Several lines of evidence suggest that these states rely upon declarative learning and memory processes, which are based primarily in the medial temporal lobes (MTL). The MTL, and particularly the hippocampus, is unusual in that it is especially vulnerable to insult. Consequently, we examine here the impact on hunger and satiety of conditions that: (1) are central to ingestive behaviour and where there is evidence of MTL pathology (i.e., habitual consumption of a Western-style diet, obesity, and anorexia nervosa); and (2) where there is overwhelming evidence of MTL pathology, but where ingestive behaviour is not thought central (i.e., temporal lobe epilepsy and post-traumatic stress disorder). While for some of these conditions the evidence base is currently limited, the general conclusion is that MTL impairment is linked, sometimes strongly, to dysfunctional hunger and satiety. This focus on the MTL, and declarative learning and memory processes, has implications for the development of alternative treatment approaches for the regulation of appetite.

Inhibition of PTEN-induced kinase 1 autophosphorylation may assist in preventing epileptogenesis induced by pentylenetetrazol

PTEN-induced kinase 1 (PINK1) autophosphorylation-triggered mitophagy is the main mitophagic pathway in the nervous system. Moreover, multiple studies have confirmed that mitophagy is closely related to the occurrence and development of epilepsy. Therefore, we speculated that the PINK1 autophosphorylation may be involved in epileptogenesis by mediating mitophagic pathway. This study aimed to explore the contribution of activated PINK1 to epileptogenesis induced by pentylenetetrazol (PTZ) in Sprague‒Dawley rats. During PTZ-induced epileptogenesis, the levels of phosphorylated PINK1 were increased, accompanied by elevated mitophagy, mitochondria oxidative stress and neuronal damage. After microRNA intervention targeting translocase outer mitochondrial membrane 7 (TOM7) or overlapping with the m-AAA protease 1 homolog (OMA1), the levels of PINK1 phosphorylation, mitophagy, mitochondrial oxidative stress, neuronal injury were observed in the rats with induced epileptogenesis. Furthermore, inhibiting of the expression of TOM7, a positive regulator of PINK1 autophosphorylation, reversed the increase in PINK1 phosphorylation and alleviated mitophagy, neuronal injury, thereby preventing epileptogenesis. In contrast, reducing the levels of OMA1, a negative regulator of PINK1 autophosphorylation, led to increased phosphorylation of PINK1, accompanied by aggravated neuronal injury and ultimately, epileptogenesis. This study confirmed the contribution of activated PINK1 to PTZ-induced epileptogenesis and suggested that the inhibition of PINK1 autophosphorylation may assist in preventing epileptogenesis.

Neurodynamical Computing at the Information Boundaries of Intelligent Systems

Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies-properly conceived as reentrant dynamical flows and not merely as identified groups of neurons-may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.

Configuration and dynamics of dominant inspiratory multineuronal activity patterns during eupnea and gasping generation in vitro

The pre-Bötzinger complex (preBötC), located within the ventral respiratory column, produces inspiratory bursts in varying degrees of synchronization/amplitude. This wide range of population burst patterns reflects the flexibility of the preBötC neurons, which is expressed in variations in the onset/offset times of their activations and their activity during the population bursts, with respiratory neurons exhibiting a large cycle-to-cycle timing jitter both at the population activity onset and at the population activity peak, suggesting that respiratory neurons are stochastically activated before and during the inspiratory bursts. However, it is still unknown whether this stochasticity is maintained while evaluating the coactivity of respiratory neuronal ensembles. Moreover, the preBötC topology also remains unknown. In this study, by simultaneously recording tens of preBötC neurons and using coactivation analysis during the inspiratory periods, we found that the preBötC has a scale-free configuration (mixture of not many highly connected nodes, hubs, with abundant poorly connected elements) exhibiting the rich-club phenomenon (hubs more likely interconnected with each other). PreBötC neurons also produce multineuronal activity patterns (MAPs) that are highly stable and change during the hypoxia-induced reconfiguration. Moreover, preBötC contains a coactivating core network shared by all its MAPs. Finally, we found a distinctive pattern of sequential coactivation of core network neurons at the beginning of the inspiratory periods, indicating that, when evaluated at the multicellular level, the coactivation of respiratory neurons seems not to be stochastic.NEW & NOTEWORTHY By means of multielectrode recordings of preBötC neurons, we evaluated their configuration in normoxia and hypoxia, finding that the preBötC exhibits a scale-free configuration with a rich-club phenomenon. preBötC neurons produce multineuronal activity patterns that are highly stable but change during hypoxia. The preBötC contains a coactivating core network that exhibit a distinctive pattern of coactivation at the beginning of inspirations. These results reveal some network basis of inspiratory rhythm generation and its reconfiguration during hypoxia.

Rewiring of Memory Circuits: Connecting Adult Newborn Neurons With the Help of Microglia

New neurons are continuously generated from stem cells and integrated into the adult hippocampal circuitry, contributing to memory function. Several environmental, cellular, and molecular factors regulate the formation of new neurons, but the mechanisms that govern their incorporation into memory circuits are less explored. Herein we will focus on microglia, the resident immune cells of the CNS, which modulate the production of new neurons in the adult hippocampus and are also well suited to participate in their circuit integration. Microglia may contribute to the refinement of brain circuits during development and exert a role in physiological and pathological conditions by regulating axonal and dendritic growth; promoting the formation, elimination, and relocation of synapses; modulating excitatory synaptic maturation; and participating in functional synaptic plasticity. Importantly, microglia are able to sense subtle changes in their environment and may use this information to differently modulate hippocampal wiring, ultimately impacting on memory function. Deciphering the role of microglia in hippocampal circuitry constant rewiring will help to better understand the influence of microglia on memory function.

Altered brain structural topological properties in type 2 diabetes mellitus patients without complications

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a risk factor for cognitive dysfunction, and white matter (WM) microstructural impairments play a critical role in T2DM-related cognitive decline. Disruptions to the WM have been detected in T2DM patients before clinical diagnosis of cognitive dysfunction. Herein, we investigated changes in brain structural topological properties and their correlation with behavior in T2DM patients without complications.

METHODS

Diffusion tensor imaging (DTI) structural network topological analysis was performed on T2DM patients and healthy controls. Intergroup differences in global and nodal parameters were analyzed, and correlations between the network parameters and behavioral performance were tested.

RESULTS

Type 2 diabetes mellitus patients exhibited preserved small-world properties, but altered nodal properties, including decreased efficiency in the right hippocampus, right amygdala, left pallidum, left postcentral gyrus, and right pole of the superior temporal gyrus, and increased degree in the right inferior frontal gyrus. Correlations were also found between the altered global and nodal parameters and behavioral performance.

CONCLUSIONS

The results verified the existence of WM structural network changes and the association between structural properties and cognitive state in T2DM patients before the occurrence of complications. Research of structural properties may contribute to our understanding of the intrinsic links between T2DM and cognition.

Network supporting contextual fear learning after dorsal hippocampal damage has increased dependence on retrosplenial cortex

Hippocampal damage results in profound retrograde, but no anterograde amnesia in contextual fear conditioning (CFC). Although the content learned in the latter have been discussed, alternative regions supporting CFC learning were seldom proposed and never empirically addressed. Here, we employed network analysis of pCREB expression quantified from brain slices of rats with dorsal hippocampal lesion (dHPC) after undergoing CFC session. Using inter-regional correlations of pCREB-positive nuclei between brain regions, we modelled functional networks using different thresholds. The dHPC network showed small-world topology, equivalent to SHAM (control) network. However, diverging hubs were identified in each network. In a direct comparison, hubs in both networks showed consistently higher centrality values compared to the other network. Further, the distribution of correlation coefficients was different between the groups, with most significantly stronger correlation coefficients belonging to the SHAM network. These results suggest that dHPC network engaged in CFC learning is partially different, and engage alternative hubs. We next tested if pre-training lesions of dHPC and one of the new dHPC network hubs (perirhinal, Per; or disgranular retrosplenial, RSC, cortices) would impair CFC. Only dHPC-RSC, but not dHPC-Per, impaired CFC. Interestingly, only RSC showed a consistently higher centrality in the dHPC network, suggesting that the increased centrality reflects an increased functional dependence on RSC. Our results provide evidence that, without hippocampus, the RSC, an anatomically central region in the medial temporal lobe memory system might support CFC learning and memory.

Shared Functions of Perirhinal and Parahippocampal Cortices: Implications for Cognitive Aging

A predominant view of perirhinal cortex (PRC) and postrhinal/parahippocampal cortex (POR/PHC) function contends that these structures are tuned to represent objects and spatial information, respectively. However, known anatomical connectivity, together with recent electrophysiological, neuroimaging, and lesion data, indicate that both brain areas participate in spatial and nonspatial processing. Instead of content-based organization, the PRC and PHC/POR may participate in two computationally distinct cortical-hippocampal networks: one network that is tuned to process coarse information quickly, forming gist-like representations of scenes/environments, and a second network tuned to process information about the specific sensory details that are necessary for discrimination across sensory modalities. The available data suggest that the latter network may be more vulnerable in advanced age.

Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson's disease

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson's disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data.

Graph Theoretic and Motif Analyses of the Hippocampal Neuron Type Potential Connectome

We computed the potential connectivity map of all known neuron types in the rodent hippocampal formation by supplementing scantly available synaptic data with spatial distributions of axons and dendrites from the open-access knowledge base Hippocampome.org. The network that results from this endeavor, the broadest and most complete for a mammalian cortical region at the neuron-type level to date, contains more than 3200 connections among 122 neuron types across six subregions. Analyses of these data using graph theory metrics unveil the fundamental architectural principles of the hippocampal circuit. Globally, we identify a highly specialized topology minimizing communication cost; a modular structure underscoring the prominence of the trisynaptic loop; a core set of neuron types serving as information-processing hubs as well as a distinct group of particular antihub neurons; a nested, two-tier rich club managing much of the network traffic; and an innate resilience to random perturbations. At the local level, we uncover the basic building blocks, or connectivity patterns, that combine to produce complex global functionality, and we benchmark their utilization in the circuit relative to random networks. Taken together, these results provide a comprehensive connectivity profile of the hippocampus, yielding novel insights on its functional operations at the computationally crucial level of neuron types.