Parallel Pathways Provide Hippocampal Spatial Information to Prefrontal Cortex.

Long-range synaptic connections define how information flows through neuronal networks. Here, we combined retrograde and anterograde trans-synaptic viruses to delineate areas that exert direct and indirect influence over the dorsal and ventral prefrontal cortex (PFC) of the rat (both sexes). Notably, retrograde tracing using pseudorabies virus (PRV) revealed that both dorsal and ventral areas of the PFC receive prominent disynaptic input from the dorsal CA3 (dCA3) region of the hippocampus. The PRV experiments also identified candidate anatomical relays for this disynaptic pathway, namely, the ventral hippocampus, lateral septum, thalamus, amygdala, and basal forebrain. To determine the viability of each of these relays, we performed three additional experiments. In the first, we injected the retrograde monosynaptic tracer Fluoro-Gold into the PFC and the anterograde monosynaptic tracer Fluoro-Ruby into the dCA3 to confirm the first-order connecting areas and revealed several potential relay regions between the PFC and dCA3. In the second, we combined PRV injection in the PFC with polysynaptic anterograde viral tracer (HSV-1) in the dCA3 to reveal colabeled connecting neurons, which were evident only in the ventral hippocampus. In the third, we combined retrograde adeno-associated virus (AAV) injections in the PFC with an anterograde AAV in the dCA3 to reveal anatomical relay neurons in the ventral hippocampus and dorsal lateral septum. Together, these findings reveal parallel disynaptic pathways from the dCA3 to the PFC, illuminating a new anatomical framework for understanding hippocampal-prefrontal interactions. We suggest that the representation of context and space may be a universal feature of prefrontal function.SIGNIFICANCE STATEMENT The known functions of the prefrontal cortex are shaped by input from multiple brain areas. We used transneuronal viral tracing to discover multiple prominent disynaptic pathways through which the dorsal hippocampus (specifically, the dorsal CA3) has the potential to shape the actions of the prefrontal cortex. The demonstration of neuronal relays in the ventral hippocampus and lateral septum presents a new foundation for understanding long-range influences over prefrontal interactions, including the specific contribution of the dorsal CA3 to prefrontal function.

Distinct and Dissociable EEG Networks Are Associated With Recovery of Cognitive Function Following Anesthesia-Induced Unconsciousness.

The temporal trajectories and neural mechanisms of recovery of cognitive function after a major perturbation of consciousness is of both clinical and neuroscientific interest. The purpose of the present study was to investigate network-level changes in functional brain connectivity associated with the recovery and return of six cognitive functions after general anesthesia. High-density electroencephalograms (EEG) were recorded from healthy volunteers undergoing a clinically relevant anesthesia protocol (propofol induction and isoflurane maintenance), and age-matched healthy controls. A battery of cognitive tests (motor praxis, visual object learning test, fractal-2-back, abstract matching, psychomotor vigilance test, digital symbol substitution test) was administered at baseline, upon recovery of consciousness (ROC), and at half-hour intervals up to 3 h following ROC. EEG networks were derived using the strength of functional connectivity measured through the weighted phase lag index (wPLI). A partial least squares (PLS) analysis was conducted to assess changes in these networks: (1) between anesthesia and control groups; (2) during the 3-h recovery from anesthesia; and (3) for each cognitive test during recovery from anesthesia. Networks were maximally perturbed upon ROC but returned to baseline 30-60 min following ROC, despite deficits in cognitive performance that persisted up to 3 h following ROC. Additionally, during recovery from anesthesia, cognitive tests conducted at the same time-point activated distinct and dissociable functional connectivity networks across all frequency bands. The results highlight that the return of cognitive function after anesthetic-induced unconsciousness is task-specific, with unique behavioral and brain network trajectories of recovery.

Differential classification of states of consciousness using envelope- and phase-based functional connectivity.

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.