Transplantation in the nonhuman primate MPTP model of Parkinson's disease: update and perspectives

In order to calibrate stem cell exploitation for cellular therapy in neurodegenerative diseases, fundamental and preclinical research in NHP (nonhuman primate) models is crucial. Indeed, it is consensually recognized that it is not possible to directly extrapolate results obtained in rodent models to human patients. A large diversity of neurological pathologies should benefit from cellular therapy based on neural differentiation of stem cells. In the context of this special issue of Primate Biology on NHP stem cells, we describe past and recent advances on cell replacement in the NHP model of Parkinson's disease (PD). From the different grafting procedures to the various cell types transplanted, we review here diverse approaches for cell-replacement therapy and their related therapeutic potential on behavior and function in the NHP model of PD

Brain rhythms define distinct interaction networks with differential dependence on anatomy

Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent. Thus, the rhythms defined distinct interaction networks. Importantly, networks of coherence and GC were not explained by the spatial distributions of the strengths of the rhythms. Those networks, particularly the GC networks, contained clear modules, with typically one dominant rhythm per module. To understand how this distinctiveness and modularity arises on a common anatomical backbone, we correlated, across 91 area pairs, the metrics of functional interaction with those of anatomical projection strength. Anatomy was primarily related to coherence and GC, with the largest effect sizes for GC. The correlation differed markedly between rhythms, being less pronounced for the beta and strongest for the gamma rhythm

The statistical neuroanatomy of frontal networks in the macaque

We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 68 input areas representing exterosensory, chemosensory, motor, limbic, and other frontal inputs. The analysis revealed a set of statistically robust clusters. We used these clusters to divide the frontal areas into 5 groups, including ventral-lateral, ventral-medial, dorsal-medial, dorsal-lateral, and caudal-orbital groups. Each of these groups was defined by a unique set of inputs. This organization provides insight into the differential roles of each group of areas and suggests a gradient by which orbital and ventral-medial areas may be responsible for decision-making processes based on emotion and primary reinforcers, and lateral frontal areas are more involved in integrating affective and rational information into a common framework

Early Presymptomatic and Long-Term Changes of Rest Activity Cycles and Cognitive Behavior in a MPTP-Monkey Model of Parkinson's Disease

It is increasingly recognized that non-motor symptoms are a prominent feature of Parkinson's disease and in the case of cognitive deficits can precede onset of the characteristic motor symptoms. Here, we examine in 4 monkeys chronically treated with low doses of the neurotoxin MPTP the early and long-term alterations of rest-activity rhythms in relationship to the appearance of motor and cognitive symptoms.Behavioral activity recordings as well as motor and cognitive assessments were carried out continuously and in parallel before, during and for several months following MPTP-treatment (12–56 weeks). Cognitive abilities were assessed using a task that is dependent on the functional integrity of the fronto-striatal axis. Rest-activity cycles were monitored continuously using infrared movement detectors of locomotor activity. Motor impairment was evaluated using standardized scales for primates. Results show that MPTP treatment led to an immediate alteration (within one week) of rest-activity cycles and cognitive deficits. Parkinsonian motor deficits only became apparent 3 to 5 weeks after initiating chronic MPTP administration. In three of the four animals studied, clinical scores returned to control levels 5–7 weeks following cessation of MPTP treatment. In contrast, both cognitive deficits and chronobiological alterations persisted for many months. Levodopa treatment led to an improvement of cognitive performance but did not affect rest-activity rhythms in the two cases tested.Present results show that i) changes in the rest activity cycles constituted early detectable consequences of MPTP treatment and, along with cognitive alterations, characterize the presymptomatic stage; ii) following motor recovery there is a long-term persistence of non-motor symptoms that could reflect differential underlying compensatory mechanisms in these domains; iii) the progressive MPTP-monkey model of presymptomatic ongoing parkinsonism offers possibilities for in-depth studies of early non-motor symptoms including sleep alterations and cognitive deficits

Weight Consistency Specifies Regularities of Macaque Cortical Networks

To what extent cortical pathways show significant weight differences and whether these differences are consistent across animals (thereby comprising robust connectivity profiles) is an important and unresolved neuroanatomical issue. Here we report a quantitative retrograde tracer analysis in the cynomolgus macaque monkey of the weight consistency of the afferents of cortical areas across brains via calculation of a weight index (fraction of labeled neurons, FLN). Injection in 8 cortical areas (3 occipital plus 5 in the other lobes) revealed a consistent pattern: small subcortical input (1.3% cumulative FLN), high local intrinsic connectivity (80% FLN), high-input form neighboring areas (15% cumulative FLN), and weak long-range corticocortical connectivity (3% cumulative FLN). Corticocortical FLN values of projections to areas V1, V2, and V4 showed heavy-tailed, lognormal distributions spanning 5 orders of magnitude that were consistent, demonstrating significant connectivity profiles. These results indicate that 1) connection weight heterogeneity plays an important role in determining cortical network specificity, 2) high investment in local projections highlights the importance of local processing, and 3) transmission of information across multiple hierarchy levels mainly involves pathways having low FLN values

Identification and Classification of Hubs in Brain Networks

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles

Accelerating the Evolution of Nonhuman Primate Neuroimaging

Nonhuman primate neuroimaging is on the cusp of a transformation, much in the same way its human counterpart was in 2010, when the Human Connectome Project was launched to accelerate progress. Inspired by an open data-sharing initiative, the global community recently met and, in this article, breaks through obstacles to define its ambitions