A framework for precision "dosing" of mental healthcare services: algorithm development and clinical pilot.

BACKGROUND: One in five adults in the US experience mental illness and over half of these adults do not receive treatment. In addition to the access gap, few innovations have been reported for ensuring the right level of mental healthcare service is available at the right time for individual patients. METHODS: Historical observational clinical data was leveraged from a virtual healthcare system. We conceptualize mental healthcare services themselves as therapeutic interventions and develop a prototype computational framework to estimate their potential longitudinal impacts on depressive symptom severity, which is then used to assess new treatment schedules and delivered to clinicians via a dashboard. We operationally define this process as "session dosing": 497 patients who started treatment with severe symptoms of depression between November 2020 and October 2021 were used for modeling. Subsequently, 22 mental health providers participated in a 5-week clinical quality improvement (QI) pilot, where they utilized the prototype dashboard in treatment planning with 126 patients. RESULTS: The developed framework was able to resolve patient symptom fluctuations from their treatment schedules: 77% of the modeling dataset fit criteria for using the individual fits for subsequent clinical planning where five anecdotal profile types were identified that presented different clinical opportunities. Based on initial quality thresholds for model fits, 88% of those individuals were identified as adequate for session optimization planning using the developed dashboard, while 12% supported more thorough treatment planning (e.g. different treatment modalities). In the clinical pilot, 90% of clinicians reported using the dashboard a few times or more per member. Although most clinicians (67.5%) either rarely or never used the dashboard to change session types, numerous other discussions were enabled, and opportunities for automating session recommendations were identified. CONCLUSIONS: It is possible to model and identify the extent to which mental healthcare services can resolve depressive symptom severity fluctuations. Implementation of one such prototype framework in a real-world clinic represents an advancement in mental healthcare treatment planning; however, investigations to assess which clinical endpoints are impacted by this technology, and the best way to incorporate such frameworks into clinical workflows, are needed and are actively being pursued.

Coding of social novelty in the hippocampal CA2 region and its disruption and rescue in a 22q11.2 microdeletion mouse model.

The hippocampal CA2 region is essential for social memory. To determine whether CA2 activity encodes social interactions, we recorded extracellularly from CA2 pyramidal neurons (PNs) in male mice during social behavior. Although CA2 neuronal firing showed only weak spatial selectivity, it accurately encoded contextual changes and distinguished between a novel and a familiar mouse. In the Df(16)A+/- mouse model of the human 22q11.2 microdeletion, which confers a 30-fold increased risk of schizophrenia, CA2 social coding was impaired, consistent with the social memory deficit observed in these mice; in contrast, spatial coding accuracy was greatly enhanced. CA2 PNs were previously found to be hyperpolarized in Df(16)A+/- mice, likely due to upregulation of TREK-1 K+ current. We found that TREK-1 blockade rescued social memory and CA2 social coding in Df(16)A+/- mice, supporting a crucial role for CA2 in the normal encoding of social stimuli and in social behavioral dysfunction in disease.

Hippocampal Neural Circuits Respond to Optogenetic Pacing of Theta Frequencies by Generating Accelerated Oscillation Frequencies.

Biological oscillations can be controlled by a small population of rhythmic pacemaker cells, or in the brain, they also can emerge from complex cellular and circuit-level interactions. Whether and how these mechanisms are combined to give rise to oscillatory patterns that govern cognitive function are not well understood. For example, the activity of hippocampal networks is temporally coordinated by a 7- to 9-Hz local field potential (LFP) theta rhythm, yet many individual cells decouple from the LFP frequency to oscillate at frequencies ∼1 Hz higher. To better understand the network interactions that produce these complex oscillatory patterns, we asked whether the relative frequency difference between LFP and individual cells is retained when the LFP frequency is perturbed experimentally. We found that rhythmic optogenetic stimulation of medial septal GABAergic neurons controlled the hippocampal LFP frequency outside of the endogenous theta range, even during behavioral states when endogenous mechanisms would otherwise have generated 7- to 9-Hz theta oscillations. While the LFP frequency matched the optogenetically induced stimulation frequency, the oscillation frequency of individual hippocampal cells remained broadly distributed, and in a subset of cells including interneurons, it was accelerated beyond the new base LFP frequency. The inputs from septal GABAergic neurons to the hippocampus, therefore, do not appear to directly control the cellular oscillation frequency but rather engage cellular and circuit mechanisms that accelerate the rhythmicity of individual cells. Thus, theta oscillations are an example of cortical oscillations that combine inputs from a subcortical pacemaker with local computations to generate complex oscillatory patterns that support cognitive functions.