Organization of afferents to the orbitofrontal cortex in the rat.

The prefrontal cortex (PFC) is usually defined as the frontal cortical area receiving a mediodorsal thalamic (MD) innervation. Certain areas in the medial wall of the rat frontal area receive a MD innervation. A second frontal area that is the target of MD projections is located dorsal to the rhinal sulcus and often referred to as the orbitofrontal cortex (OFC). Both the medial PFC and OFC are comprised of a large number of cytoarchitectonic regions. We assessed the afferent innervation of the different areas of the OFC, with a focus on projections arising from the mediodorsal thalamic nucleus, the basolateral nucleus of the amygdala, and the midbrain dopamine neurons. Although there are specific inputs to various OFC areas, a simplified organizational scheme could be defined, with the medial areas of the OFC receiving thalamic inputs, the lateral areas of the OFC being the recipient of amygdala afferents, and a central zone that was the target of midbrain dopamine neurons. Anterograde tracer data were consistent with this organization of afferents, and revealed that the OFC inputs from these three subcortical sites were largely spatially segregated. This spatial segregation suggests that the central portion of the OFC (pregenual agranular insular cortex) is the only OFC region that is a prefrontal cortical area, analogous to the prelimbic cortex in the medial prefrontal cortex. These findings highlight the heterogeneity of the OFC, and suggest possible functional attributes of the three different OFC areas.

Connecting imaging mass spectrometry and magnetic resonance imaging-based anatomical atlases for automated anatomical interpretation and differential analysis.

Imaging mass spectrometry (IMS) is a molecular imaging technology that can measure thousands of biomolecules concurrently without prior tagging, making it particularly suitable for exploratory research. However, the data size and dimensionality often makes thorough extraction of relevant information impractical. To help guide and accelerate IMS data analysis, we recently developed a framework that integrates IMS measurements with anatomical atlases, opening up opportunities for anatomy-driven exploration of IMS data. One example is the automated anatomical interpretation of ion images, where empirically measured ion distributions are automatically decomposed into their underlying anatomical structures. While offering significant potential, IMS-atlas integration has thus far been restricted to the Allen Mouse Brain Atlas (AMBA) and mouse brain samples. Here, we expand the applicability of this framework by extending towards new animal species and a new set of anatomical atlases retrieved from the Scalable Brain Atlas (SBA). Furthermore, as many SBA atlases are based on magnetic resonance imaging (MRI) data, a new registration pipeline was developed that enables direct non-rigid IMS-to-MRI registration. These developments are demonstrated on protein-focused FTICR IMS measurements from coronal brain sections of a Parkinson's disease (PD) rat model. The measurements are integrated with an MRI-based rat brain atlas from the SBA. The new rat-focused IMS-atlas integration is used to perform automated anatomical interpretation and to find differential ions between healthy and diseased tissue. IMS-atlas integration can serve as an important accelerator in IMS data exploration, and with these new developments it can now be applied to a wider variety of animal species and modalities. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.