Monkey Prefrontal Cortex Research Articles

Neural Correlates of Strategy Switching in the Macaque Orbital Prefrontal Cortex.

We can adapt flexibly to environment changes and search for the most appropriate rule to a context. The orbital prefrontal cortex (PFo) has been associated with decision making, rule generation and maintenance, and more generally has been considered important for behavioral flexibility. To better understand the neural mechanisms underlying the flexible behavior, we studied the ability to generate a switching signal in monkey PFo when a strategy is changed. In the strategy task, we used a visual cue to instruct two male rhesus monkeys either to repeat their most recent choice (i.e., stay strategy) or to change it (i.e., shift strategy). To identify the strategy switching-related signal, we compared nonswitch and switch trials, which cued the same or a different strategy from the previous trial, respectively. We found that the switching-related signal emerged during the cue presentation and it was combined with the strategy signal in a subpopulation of cells. Moreover, the error analysis showed that the activity of the switch-related cells reflected whether the monkeys erroneously switched or not the strategy, rather than what was required for that trial. The function of the switching signal could be to prompt the use of different strategies when older strategies are no longer appropriate, conferring the ability to adapt flexibly to environmental changes. In our task, the switching signal might contribute to the implementation of the strategy cued, overcoming potential interference effects from the strategy previously cued. Our results support the idea that ascribes to PFo an important role for behavioral flexibility.SIGNIFICANCE STATEMENT We can flexibly adapt our behavior to a changing environment. One of the prefrontal areas traditionally associated with the ability to adapt to new contingencies is the orbital prefrontal cortex (PFo). We analyzed the switching related activity using a strategy task in which two rhesus monkeys were instructed by a visual cue either to repeat or change their most recent choice, respectively using a stay or a shift strategy. We found that PFo neurons were modulated by the strategy switching signal, pointing to the importance of PFo in behavioral flexibility by generating control over the switching of strategies.

Synaptic distributions of pS214-tau in rhesus monkey prefrontal cortex are associated with spine density, but not with cognitive decline.

Female rhesus monkeys and women are subject to age- and menopause-related deficits in working memory, an executive function mediated by the dorsolateral prefrontal cortex (dlPFC). Long-term cyclic administration of 17β-estradiol improves working memory, and restores highly plastic axospinous synapses within layer III dlPFC of aged ovariectomized monkeys. In this study, we tested the hypothesis that synaptic distributions of tau protein phosphorylated at serine 214 (pS214-tau) are altered with age or estradiol treatment, and couple to working memory performance. First, ovariectormized young and aged monkeys received vehicle or estradiol treatment, and were tested on the delayed response (DR) test of working memory. Serial section electron microscopic immunocytochemistry was then performed to quantitatively assess the subcellular synaptic distributions of pS214-tau. Overall, the majority of synapses contained pS214-tau immunogold particles, which were predominantly localized to the cytoplasm of axon terminals. pS214-tau was also abundant within synaptic and cytoplasmic domains of dendritic spines. The density of pS214-tau immunogold within the active zone, cytoplasmic, and plasmalemmal domains of axon terminals, and subjacent to the postsynaptic density within the subsynaptic domains of dendritic spines, were each reduced with age. None of the variables examined were directly linked to cognitive status, but a high density of pS214-tau immunogold particles within presynaptic cytoplasmic and plasmalemmal domains, and within postsynaptic subsynaptic and plasmalemmal domains, accompanied high synapse density. Together, these data support a possible physiological, rather than pathological, role for pS214-tau in the modulation of synaptic morphology in monkey dlPFC.

Brodmann Areas 8 and 9 Including the Frontal Eye Field

Based on cytoarchitectonic analyses, Brodmann assigned numbers 8 and 9 to certain areas of the dorsal and medial prefrontal cortex (PFC) in humans and monkeys. Petrides and Pandya re-analyzed the cytoarchitectures of the human and monkey PFCs, and proposed slightly different brain maps for both species. They assigned numbers 8, 9 and 9/46 to the areas that were originally named areas 8 and 9. Areas 8 and 9 have both lateral and medial regions respectively. The lateral area 8 is important for conditional discrimination learning. The frontal eye field which occupies the most caudal region of area 8, is responsible for visual attention and control of eye movements. The lateral area 9 and area 9/46 are functionally similar to area 46 and play important roles in executive control. The dorsomedial prefrontal cortex (DMPFC) comprises the medial regions of areas 8 and 9 and is related to "Theory of Mind" and social cognition. The DMPFC is also known to show "default mode of brain activity" (i.e., more activity during rest than during cognitive task).

PM369. Shift in ErbB4 Splicing is Associated with Developmental Pruning of Excitatory Synapses on Parvalbumin Interneurons in Monkey Prefrontal Cortex

PM369. Shift in ErbB4 Splicing is Associated with Developmental Pruning of Excitatory Synapses on Parvalbumin Interneurons in Monkey Prefrontal Cortex

"Subpial Fan Cell" - A Class of Calretinin Neuron in Layer 1 of Adult Monkey Prefrontal Cortex.

Layer 1 of the cortex contains populations of neurochemically distinct neurons and afferent fibers which markedly affect neural activity in the apical dendritic tufts of pyramidal cells. Understanding the causal mechanisms requires knowledge of the cellular architecture and synaptic organization of layer 1. This study has identified eight morphological classes of calretinin immunopositive (CRet+) neurons (including Cajal-Retzius cells) in layer 1 of the prefrontal cortex (PFC) in adult monkey (Macaca fasicularis), with a distinct class — termed “subpial fan (SPF) cell” — described in detail. SPF cells were rare horizontal unipolar CRet+ cells located directly beneath the pia with a single thick primary dendrite that branched into a characteristic fan-like dendritic tree tangential to the pial surface. Dendrites had spines, filamentous processes and thorny branchlets. SPF cells lay millimeters apart with intralaminar axons that ramified widely in upper layer 1. Such cells were GABA immunonegative (-) and occurred in areas beyond PFC. Interspersed amidst SPF cells displaying normal structural integrity were degenerating CRet+ neurons (including SPF cells) and clumps of lipofuscin-rich cellular debris. The number of degenerating SPF cells increased during adulthood. Ultrastructural analyses indicated SPF cell somata received asymmetric (A — presumed excitatory) and symmetric (S — presumed inhibitory) synaptic contacts. Proximal dendritic shafts received mainly S-type and distal shafts mostly A-type input. All dendritic thorns and most dendritic spines received both synapse types. The tangential areal density of SPF cell axonal varicosities varied radially from parent somata — with dense clusters in more distal zones. All boutons formed A-type contacts with CRet- structures. The main post-synaptic targets were dendritic shafts (67%; mostly spine-bearing) and dendritic spines (24%). SPF-SPF cell innervation was not observed. Morphometry of SPF cells indicated a unique class of CRet+/GABA- neuron in adult monkey PFC — possibly a subtype of persisting Cajal-Retzius cell. The distribution and connectivity of SPF cells suggest they act as integrative hubs in upper layer 1 during postnatal maturation. The main synaptic output of SPF cells likely provides a transminicolumnar excitatory influence across swathes of apical dendritic tufts — thus affecting information processing in discrete patches of layer 1 in adult monkey PFC.

Differential Expression of Genes Involved in Inflammatory Immune Response and Protein Ubiquitination in the Prefrontal Cortex of Rhesus Macaque with High and Low Lutein Content

Lutein, a carotenoid with antioxidant and anti‐inflammatory functions, accumulates in the primate brain. Studies have shown that brain levels of lutein are more consistently related to better cognitive test scores in humans than other antioxidants found in higher concentrations in the brain, such as vitamin E. Supplementation with lutein can improve verbal fluency, memory scores, and rates of learning in older adults. However, the mechanism by which lutein functions in cognition is unclear. The aim of this study was to determine the relationship between lutein concentration and gene expression profiles in rhesus macaque brain. Brain tissue was dissected from monkeys fed a chow diet containing lutein (~16 μmol/kg diet). Next generation RNA sequencing was used to determine differentially expressed genes in the prefrontal cortex of monkeys (11–13y) with high lutein content (mean=34.5 pg/mg wet weight, n=3) versus those with low lutein content (mean=11.8 pg/mg wet weight, n=3). Lutein concentrations were determined in these brain samples using HPLC. A total of 415 genes were differentially expressed between the two groups. Ingenuity Pathway Analysis (IPA) revealed the up‐regulation of pro‐inflammatory immune response pathways, such as chemokine signaling, antigen presentation, leukocyte extravasation, and neuropathic pain signaling, in brains with low lutein content. A total of 16 genes were upregulated in this pro‐inflammatory network, with specific genes of interest including beta‐2‐microglobulin and p38 MAPK (1.5 fold change for each), which are both associated with age‐related cognitive impairment and neurodegeneration. Additionally, up‐regulation of the protein ubiquitination pathway (9 genes), a hallmark of Alzheimer's disease, was observed in brains with low lutein content. These results indicate that lutein may play a role in suppressing neuroinflammation at the transcription level, and provide the first steps towards understanding the mechanisms underlying the beneficial effect of lutein on cognition.Support or Funding InformationThis work was supported by grants from Abbott Nutrition through the Center for Nutrition, Learning, and Memory at the University of Illinois, USDA (58‐1950‐4‐003), and NIH grant P51OD011092 to the Oregon National Primate Research Center

Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection.

Humans, monkeys, and other animals are considered to have the cognitive ability to use functional categories--that is, stimulus groups based on functional equivalence independent of physical properties. To investigate the underlying neural mechanisms of the use of functional categories, we recorded single-unit activity in the prefrontal cortex of monkeys performing a behavioral task in which the rule-dependent usage of functional category was needed to select an appropriate response. We found a neural correlate of functional categories on the single-neuron level and found that category information is coded independently of other task-relevant information such as rule and contingency information. Analysis of the time course of the information activation suggested that contingency information used for action selection is derived by integrating incoming category information with rule information maintained throughout a session. Such neural computation can be considered as the neural background of flexible behavioral control based on category and rule.

Behavioral response inhibition and maturation of goal representation in prefrontal cortex after puberty

Executive functions including behavioral response inhibition mature after puberty, in tandem with structural changes in the prefrontal cortex. Little is known about how activity of prefrontal neurons relates to this profound cognitive development. To examine this, we tracked neuronal responses of the prefrontal cortex in monkeys as they transitioned from puberty into adulthood and compared activity at different developmental stages. Performance of the antisaccade task greatly improved in this period. Among neural mechanisms that could facilitate it, reduction of stimulus-driven activity, increased saccadic activity, or enhanced representation of the opposing goal location, only the latter was evident in adulthood. Greatly accentuated in adults, this neural correlate of vector inversion may be a prerequisite to the formation of a motor plan to look away from the stimulus. Our results suggest that the prefrontal mechanisms that underlie mature performance on the antisaccade task are more strongly associated with forming an alternative plan of action than with suppressing the neural impact of the prepotent stimulus.

Diverse Synaptic Distributions of G Protein-coupled Estrogen Receptor 1 in Monkey Prefrontal Cortex with Aging and Menopause.

Age- and menopause-related impairment in working memory mediated by the dorsolateral prefrontal cortex (dlPFC) occurs in humans and nonhuman primates. Long-term cyclic 17β-estradiol treatment rescues cognitive deficits in aged ovariectomized rhesus monkeys while restoring highly plastic synapses. Here we tested whether distributions of G protein-coupled estrogen receptor 1 (GPER1) within monkey layer III dlPFC synapses are sensitive to age and estradiol, and coupled to cognitive function. Ovariectomized young and aged monkeys administered vehicle or estradiol were first tested on a delayed response test of working memory. Then, quantitative serial section immunoelectron microscopy was used to determine the distributions of synaptic GPER1. GPER1-containing nonperforated axospinous synapse density was reduced with age, and partially restored with estrogen treatment. The majority of synapses expressed GPER1, which was predominately localized to presynaptic cytoplasm and mitochondria. GPER1 was also abundant at plasmalemmas, and within cytoplasmic and postsynaptic density (PSD) domains of dendritic spines. GPER1 levels did not differ with age or treatment, and none of the variables examined were tightly associated with cognitive function. However, greater representation of GPER1 subjacent to the PSD accompanied higher synapse density. These data suggest that GPER1 is positioned to support diverse functions key to synaptic plasticity in monkey dlPFC.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits.

Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks.

Capturing the temporal evolution of choice across prefrontal cortex

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making.

Self-organization to sub-criticality

Human brains possess sophisticated information processing capabilities, which rely on the interactions of billions of neurons. However, it is unclear how these capabilities arise from the collective spiking dynamics. A popular hypothesis is that neural networks assume a critical state [1,2], because in models criticality maximizes information processing capabilities [3,4]. However, it has been largely overlooked that criticality in neural networks also comes with the risk of spontaneous runaway activity [5], which has been linked to epilepsy. Does the brain indeed assume a critical state, despite the risk of instability? To revisit this question, we analyzed spiking activity from awake animals, instead of more coarse measures of neural activity (population spikes, LPF, EEG, BOLD) as in most previous studies. In all recordings (rats hippocampus, cats visual cortex, and monkey prefrontal cortex), spiking activity resembled a sub-critical state, not criticality proper [6]. We confirmed these results using a novel mathematical approach that is robust to subsampling effects [7] [see Wilting & Priesemann, conference proceedings CNS 2015]. While 'self-organization' to criticality has been widely studied (e.g.[5,8]), it is unclear what mechanism allows self-organize to sub-criticality instead. Here, we demonstrate that homeostatic plasticity [9] assures that networks assume a slightly sub-critical state, independently of the initial configuration. Surprisingly, increasing the external input (stimuli) altered the set-point of the network to a more sub-critical state. Our results suggest that homeostasis allows the brain to maintain a safety margin to criticality. Thereby the brain may lose processing capability, but avoids instability.

Dopamine's Actions in Primate Prefrontal Cortex: Challenges for Treating Cognitive Disorders.

The prefrontal cortex (PFC) elaborates and differentiates in primates, and there is a corresponding elaboration in cortical dopamine (DA). DA cells that fire to both aversive and rewarding stimuli likely project to the dorsolateral PFC (dlPFC), signaling a salient event. Since 1979, we have known that DA has an essential influence on dlPFC working memory functions. DA has differing effects via D1 (D1R) versus D2 receptor (D2R) families. D1R are concentrated on dendritic spines, and D1/5R stimulation produces an inverted U-shaped dose response on visuospatial working memory performance and Delay cell firing, the neurons that generate representations of visual space. Optimal levels of D1R stimulation gate out "noise," whereas higher levels, e.g., during stress, suppress Delay cell firing. These effects likely involve hyperpolarization-activated cyclic nucleotide-gated channel opening, activation of GABA interneurons, and reduced glutamate release. Dysregulation of D1R has been related to cognitive deficits in schizophrenia, and there is a need for new, lower-affinity D1R agonists that may better mimic endogenous DA to enhance mental representations and improve cognition. In contrast to D1R, D2R are primarily localized on layer V pyramidal cell dendrites, and D2/3R stimulation speeds and magnifies the firing of Response cells, including Response Feedback cells. Altered firing of Feedback neurons may relate to positive symptoms in schizophrenia. Emerging research suggests that DA may have similar effects in the ventrolateral PFC and frontal eye fields. Research on the orbital PFC in monkeys is just beginning and could be a key area for future discoveries.

Ketamine Alters Outcome-Related Local Field Potentials in Monkey Prefrontal Cortex.

A subanesthetic dose of the noncompetitive N-methyl-d-aspartate receptor antagonist ketamine is known to induce a schizophrenia-like phenotype in humans and nonhuman primates alike. The transient behavioral changes mimic the positive, negative, and cognitive symptoms of the disease but the neural mechanisms behind these changes are poorly understood. A growing body of evidence indicates that the cognitive control processes associated with prefrontal cortex (PFC) regions relies on groups of neurons synchronizing at narrow-band frequencies measurable in the local field potential (LFP). Here, we recorded LFPs from the caudo-lateral PFC of 2 macaque monkeys performing an antisaccade task, which requires the suppression of an automatic saccade toward a stimulus and the initiation of a goal-directed saccade in the opposite direction. Preketamine injection activity showed significant differences in a narrow 20-30 Hz beta frequency band between correct and error trials in the postsaccade response epoch. Ketamine significantly impaired the animals' performance and was associated with a loss of the differences in outcome-specific beta-band power. Instead, we observed a large increase in high-gamma-band activity. Our results suggest that the PFC employs beta-band synchronization to prepare for top-down cognitive control of saccades and the monitoring of task outcome.

GABA-Synthesizing Enzymes in Calbindin and Calretinin Neurons in Monkey Prefrontal Cortex.

Non-overlapping groups of cortical γ-aminobutyric acid-releasing (GABAergic) neurons are identifiable by the presence of calbindin (CB), calretinin (CR), or parvalbumin (PV). Boutons from PV neuron subtypes are also distinguishable by differences in protein levels of the GABA-synthesizing enzymes GAD65 and GAD67. Multilabel fluorescence microscopy was used to determine if this diversity extends to boutons of CB and CR neurons in monkey prefrontal cortex. CB and CR neurons gave rise to 3 subpopulations of GAD-containing boutons: GAD65+, GAD67+, and GAD65/GAD67+. Somatostatin and vasoactive intestinal peptide-expressing neurons, subtypes of CB and CR neurons, respectively, also gave rise to these distinct bouton subpopulations. At the transcript level, CB and CR neurons contained mRNA encoding GAD67-only or both GADs. Thus, the distinct subpopulations of CB/GAD+ and CR/GAD+ boutons arise from 2 unique subtypes of CB and CR neurons. The different CB and CR GAD-expressing neurons targeted the same projection neurons and neuronal structures immunoreactive for PV, CR, or CB. These findings suggest that GABA synthesis from CB/GAD67+ and CR/GAD67+ neurons would presumably be more vulnerable to disease-associated deficits in GAD67 expression, such as in schizophrenia, than neurons that also contain GAD65.

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load.

Frequency-specific hippocampal-prefrontal interactions during associative learning.

Much of our knowledge of the world depends on learning associations (for example, face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive and mnemonic abilities are akin to those of humans. We found functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, whereas HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC and increased with learning. Rapid object associative learning may occur in PFC, whereas HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands.

Differential dynamics of spatial attention, position, and color coding within the parietofrontal network.

Despite an ever growing knowledge on how parietal and prefrontal neurons encode low-level spatial and color information or higher-level information, such as spatial attention, an understanding of how these cortical regions process neuronal information at the population level is still missing. A simple assumption would be that the function and temporal response profiles of these neuronal populations match that of its constituting individual cells. However, several recent studies suggest that this is not necessarily the case and that the single-cell approach overlooks dynamic changes in how information is distributed over the neuronal population. Here, we use a time-resolved population pattern analysis to explore how spatial position, spatial attention and color information are differentially encoded and maintained in the macaque monkey prefrontal (frontal eye fields) and parietal cortex (lateral intraparietal area). Overall, our work brings about three novel observations. First, we show that parietal and prefrontal populations operate in two distinct population regimens for the encoding of sensory and cognitive information: a stationary mode and a dynamic mode. Second, we show that the temporal dynamics of a heterogeneous neuronal population brings about complementary information to that of its functional subpopulations. Thus, both need to be investigated in parallel. Last, we show that identifying the neuronal configuration in which a neuronal population encodes given information can serve to reveal this same information in a different context. All together, this work challenges common views on neural coding in the parietofrontal network.

Functional consequences of age-related morphologic changes to pyramidal neurons of the rhesus monkey prefrontal cortex.

Layer 3 (L3) pyramidal neurons in the lateral prefrontal cortex (LPFC) of rhesus monkeys exhibit dendritic regression, spine loss and increased action potential (AP) firing rates during normal aging. The relationship between these structural and functional alterations, if any, is unknown. To address this issue, morphological and electrophysiological properties of L3 LPFC pyramidal neurons from young and aged rhesus monkeys were characterized using in vitro whole-cell patch-clamp recordings and high-resolution digital reconstruction of neurons. Consistent with our previous studies, aged neurons exhibited significantly reduced dendritic arbor length and spine density, as well as increased input resistance and firing rates. Computational models using the digital reconstructions with Hodgkin-Huxley and AMPA channels allowed us to assess relationships between demonstrated age-related changes and to predict physiological changes that have not yet been tested empirically. For example, the models predict that in both backpropagating APs and excitatory postsynaptic currents (EPSCs), attenuation is lower in aged versus young neurons. Importantly, when identical densities of passive parameters and voltage- and calcium-gated conductances were used in young and aged model neurons, neither input resistance nor firing rates differed between the two age groups. Tuning passive parameters for each model predicted significantly higher membrane resistance (R m ) in aged versus young neurons. This R m increase alone did not account for increased firing rates in aged models, but coupling these R m values with subtle differences in morphology and membrane capacitance did. The predicted differences in passive parameters (or parameters with similar effects) are mathematically plausible, but must be tested empirically.

Automatic fitness function selection for compartment model optimization

During normal aging, layer 3 pyramidal neurons of the rhesus monkey prefrontal cortex (PFC) exhibit significant morphological changes, as well as higher action potential firing rates in vitro [1]. Computational modeling of individual neurons can provide insight into the ionic mechanisms underlying the increased excitability, which are currently unknown. A unique database of electrophysiological recordings and morphologic reconstructions from the same neurons, gathered through whole-cell patch clamp recording, confocal microscopy and 3D digital tracing, constrains the models. Initial modeling of six young and six aged neurons demonstrated that morphological features alone do not account entirely for the electrophysiological changes with aging [2]. It is now necessary to explore the parameter space of passive cable properties and active membrane channel conductances and kinetics, to uncover parameter combinations that reproduce the firing patterns observed in neurons of each age group. Differential Evolution (DE) is an evolutionary optimization method capable of identifying a population of candidate models throughout parameter space that closely match empirically observed firing patterns. The quality of fit achieved by an optimization is reliant on the ‘fitness functions’ used to measure the accuracy of the model. Previous neuronal compartment modeling studies using parameter optimization have introduced multiple types of fitness measurement [3], but have not described a general method to determine weights for each type. Here we introduce a novel method for automatically establishing weights of minimally correlated fitness functions, and apply it to optimization of models of young and aged PFC neurons. First, a Latin hypercube design (< 1000 points) provides a space-filling sampling of parameter space; the candidate fitness functions are then evaluated at each of these points. Second, clusters of fitness functions that are highly correlated across the hypercube are pruned to leave one representative member. Third, a principal component analysis of the remaining fitness functions across the hypercube identifies a set of fitness functions representing most of the variability in the parameter space, which are selected for use in the optimization. Fourth, weights for each selected fitness function are calculated based on the combination of coefficients for principal components and variance explained by those components. Finally, DE is conducted on the Neuroscience Gateway [4] using this automatically constructed optimization protocol. We demonstrate the method with a compartment model comprising a simplified pyramidal neuron morphology and three ion channels, optimized to data from representative young and aged neurons. Compared to a manual approach involving iterative generation of fitness functions, our novel method produces better fitting models using a tenth of the computation time. Future work will extend the automatic protocol generation to prioritize which parameters to optimize, a critical step as more ion channels are added to the model to improve fitness. This method will be used to generate morphologically detailed models of 20+ young and aged PFC neurons, predicting which ionic mechanisms underlie age-related physiological changes.