Cortical and thalamic connectivity of temporal visual cortical areas 20a and 20b of the domestic ferret (Mustela putorius furo)

The present study describes the ipsilateral and contralateral corticocortical and corticothalamic connectivity of the temporal visual areas 20a and 20b in the ferret using standard anatomical tract-tracing methods. The two temporal visual areas are strongly interconnected, but area 20a is primarily connected to the occipital visual areas, whereas area 20b maintains more widespread connections with the occipital, parietal and suprasylvian visual areas and the secondary auditory cortex. The callosal connectivity, although homotopic, consists mainly of very weak anterograde labeling which was more widespread in area 20a than area 20b. Although areas 20a and 20b are well connected with the visual dorsal thalamus, the injection into area 20a resulted in more anterograde label, whereas more retrograde label was observed in the visual thalamus following the injection into area 20b. Most interestingly, comparisons to previous connectional studies of cat areas 20a and 20b reveal a common pattern of connectivity of the temporal visual cortex in carnivores, where the posterior parietal cortex and the central temporal region (PMLS) provide network points required for dorsal and ventral stream interaction enroute to integration in the prefrontal cortex. This pattern of network connectivity is not dissimilar to that observed in primates, which highlights the ferret as a useful animal model to understand visual sensory integration between the dorsal and ventral streams. The data generated will also contribute to a connectomics database, to facilitate cross species analysis of brain connectomes and wiring principles of the brain.

Cortical and thalamic connectivity of occipital visual cortical areas 17, 18, 19, and 21 of the domestic ferret (Mustela putorius furo)

Giorgio Innocenti

The present study describes the ipsilateral and contralateral corticocortical and corticothalamic connectivity of the occipital visual areas 17, 18, 19, and 21 in the ferret using standard anatomical tract-tracing methods. In line with previous studies of mammalian visual cortex connectivity, substantially more anterograde and retrograde label was present in the hemisphere ipsilateral to the injection site compared to the contralateral hemisphere. Ipsilateral reciprocal connectivity was the strongest within the occipital visual areas, while weaker connectivity strength was observed in the temporal, suprasylvian, and parietal visual areas. Callosal connectivity tended to be strongest in the homotopic cortical areas, and revealed a similar areal distribution to that observed in the ipsilateral hemisphere, although often less widespread across cortical areas. Ipsilateral reciprocal connectivity was observed throughout the visual nuclei of the dorsal thalamus, with no contralateral connections to the visual thalamus being observed. The current study, along with previous studies of connectivity in the cat, identified the posteromedial lateral suprasylvian visual area (PMLS) as a distinct network hub external to the occipital visual areas in carnivores, implicating PMLS as a potential gateway to the parietal cortex for dorsal stream processing. These data will also contribute to a macro connectome database of the ferret brain, providing essential data for connectomics analyses and cross-species analyses of connectomes and brain connectivity matrices, as well as providing data relevant to additional studies of cortical connectivity across mammals and the evolution of cortical connectivity variation.

2019

Cortical and thalamic connectivity of posterior parietal visual cortical areas PPc and PPr of the domestic ferret (Mustela putorius furo)

Giorgio Innocenti

The present study describes the ipsilateral and contralateral cortico-cortical and cortico-thalamic connectivity of the parietal visual areas, posterior parietal caudal cortical area (PPc) and posterior parietal rostral cortical area (PPr), in the ferret using standard anatomical tract-tracing methods. The two divisions of posterior parietal cortex of the ferret are strongly interconnected, however area PPc shows stronger connectivity with the occipital and suprasylvian visual cortex, while area PPr shows stronger connectivity with the somatomotor cortex, reflecting the functional specificity of these two areas. This pattern of connectivity is mirrored in the contralateral callosal connections. In addition, PPc and PPr are connected with the visual and somatomotor nuclei of the dorsal thalamus. Numerous connectional similarities exist between the posterior parietal cortex of the ferret (PPc and PPr) and the cat (area 7 and 5), indicative of the homology of these areas within the Carnivora. These findings highlight the existence of a frontoparietal network as a shared feature of the organization of parietal cortex across Euarchontoglires and Laurasiatherians, with the degree of expression varying in relation to the expansion and areal complexity of the posterior parietal cortex. This observation indicates that the ferret is a potentially valuable experimental model animal for understanding the evolution and function of the posterior parietal cortex and the frontoparietal network across mammals. The data generated will also contribute to a connectomics database, to further cross-species analyses of connectomes and illuminate wiring principles of cortical connectivity across mammals.

2019

Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons

Alain Destexhe, Henry Markram

We review here the development of Hodgkin-Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are "fast spiking", "regular spiking", "intrinsically bursting" and "low-threshold spike" cells. For each class, we fit "minimal" HH type models to experimental data. The models contain the minimal set of voltage-dependent currents to account for the data. To obtain models as generic as possible, we used data from different preparations in vivo and in vitro, such as rat somatosensory cortex and thalamus, guinea-pig visual and frontal cortex, ferret visual cortex, cat visual cortex and cat association cortex. For two cell classes, we used automatic fitting procedures applied to several cells, which revealed substantial cell-to-cell variability within each class. The selection of such cellular models constitutes a necessary step towards building network simulations of the thalamocortical system with realistic cellular dynamical properties.

2008