Quantitative Architecture Distinguishes Prefrontal Cortical Systems in the Rhesus Monkey

Abstract

The prefrontal cortex encompasses a large and heterogeneous set of areas, whose borders have been variously mapped in different architectonic studies. Differences in cortical maps present a formidable problem in comparing data across studies and in constructing databanks on the connections and functional attributes of cortical areas. Here we used quantitative approaches to cortical mapping to investigate (i) if architectonic areas of the prefrontal cortex in adult rhesus monkeys have unique profiles and (ii) if groups of architectonic areas belonging to distinct cortical types, ranging from agranular to eulaminate, have similar features. In addition, we used multidimensional analyses to see if, and how, prefrontal areas form clusters when multiple features are considered simultaneously. We used quantitative unbiased sampling procedures to estimate the areal and laminar density of neurons, glia and neurons positive for the calcium binding proteins parvalbumin (PV), calbindin (CB) and calretinin (CR) among 21 prefrontal areas or subdivisions of areas. Neuronal density varied among the prefrontal cortices (range: 38 569 +/- 4078 to 58 708 +/- 2327 neurons/mm(3)); it was lowest in caudal orbitofrontal and medial areas (OPAll, OPro, 13, 24a, 32, M25) and highest in lateral prefrontal areas (subdivisions of areas 46 and 8). Neurons positive for PV were most prevalent in lateral prefrontal areas and least prevalent in caudal orbitofrontal and medial pre-frontal areas, whereas the opposite trend was noted for neurons that expressed CB. Neurons positive for CR did not show regional differences, and the density of glia showed small variations among prefrontal cortices. The differences among areas, along with differences in the thickness of individual areas and layers, were used to establish a quantitative profile for each area. The results showed that differences in the density of neurons, and the preponderance of neurons positive for PV and CB, were related to different architectonic types of areas found within the prefrontal cortex. Conventional as well as multiparameter statistical analyses distinguished at one extreme the agranular and dysgranular (limbic) cortices, which were characterized by prominent deep layers (V-VI), the lowest neuronal density, the highest ratio of glia/neurons, and the lowest density of PV and the highest for CB. At the other extreme, lateral eulaminate cortices were characterized by the highest density of neurons, a prominent granular layer IV, denser supragranular (II-III) than infragranular (V-VI) layers, and a balanced distribution of neurons positive for PV and CB. The results provide insights into potentially different rates of development or maturation of limbic and eulaminate prefrontal areas, and their differential vulnerability in neurological and psychiatric diseases. The quantitative methods used provide an objective approach to construct maps, address differences in nomenclature across studies, establish homologies in different species and provide a baseline to identify changes in ...

Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala

“…The terminology for the architectonic areas of the prefrontal cortices was based on the map of Barbas and Pandya (Barbas and Pandya, 1989), and the quantitative architecture of prefrontal cortices (Dombrowski et al, 2001). Borders of prefrontal architectonic areas and their layers were delineated in the same sections counterstained with thionin.…”

“…We previously demonstrated that the relative laminar distribution of connections linking pairs of prefrontal cortices is highly correlated with the relationship of the areas' structure (Barbas and Rempel-Clower, 1997). The structure of different cortical areas is assessed quantitatively by the number of identifiable layers or overall neuronal density (Dombrowski et al, 2001;Medalla and Barbas, 2006). According to the structural model, 'feedforward' connections originate from a type of cortex with more layers or higher cell density than the cortex of destination and 'feedback' connections reflect the opposite relationship.…”

“…Other lateral prefrontal areas included few, if any, labeled neurons, suggesting that lateral prefrontal projections to the amygdala originate primarily from its ventral sectors, and project preferentially to the basolateral nucleus of the amygdala. Area 10 stood apart from other areas with the sparsest projections to the amygdala emanating from either its medial or lateral sectors.Caudal orbitofrontal and caudal medial prefrontal cortices differ in their laminar organization from rostral orbitofrontal, rostral medial, and lateral prefrontal areas, so we grouped data from different areas based on their cortical type into four categories, as follows: agranular cortices included those lacking layer 4 (areas MPAll and OPAll); dysgranular areas included areas with a poorly developed layer 4 (areas 24, 25, 32, 13, and OPro); eulaminate areas included those with six layers, which were divided into two groups: eulaminate I (areas 14, 11, 10, 12, and 9) and eulaminate II cortices (areas 8 and 46), based on the distinction of their 6 layers, which is higher in eulaminate II than in I (Dombrowski et al, 2001). This analysis revealed significant differences in projection density among different types of prefrontal cortices (single-factor ANOVA, F (3,24) = 25.39, P<0.00001).…”

“…We addressed this issue by determining the relationship of prefrontal connections with the amygdala to two neurochemical classes of local inhibitory neurons that are positive for the calcium binding proteins CB and PV. These neurochemical classes of inhibitory neurons have a distinct laminar distribution in prefrontal cortices Dombrowski et al, 2001). We conducted a quantitative analysis to determine the number of CB and PV interneurons within a 75 μm radius from labeled projection neurons in four cases with BDA injection in the amygdala (cases BBr; BDr; BBl; BDl; Table 1).…”

Optimization of multiplexed bead-based cytokine immunoassays for rat serum and brain tissue

“…These IL-1 family inflammatory mediators show cell-specific patterns of production, expression and release since ligands are made principally by glia (and some neurons) while astrocytes and neurons express the signal transducing IL-1 receptor, IL-1RI (Ban et al, 1991(Ban et al, , 1993Fontana et al, 1982;Giulian et al, 1986;Lechan et al, 1990). In addition, neurons (and glia) can be differentially distributed between and within various brain regions (Dombrowski et al, 2001). Thus to most accurately characterize the net effects of IL-1 on brain function, not only should simultaneous measurements be made of six key IL-1 family cytokine proteins, but they should be made from sample volumes small enough to account for potential regional variations of the related variables.…”