Distinct recruitment of feed-forward and recurrent pathways across higher-order areas of mouse visual cortex

Cortical visual processing transforms features of the external world into increasingly complex and specialized neuronal representations. These transformations arise in part through target-specific routing of information; however, within-area computations may also contribute to area-specific function. Here, we sought to determine whether higher-order visual cortical areas LM, AL, PM, and AM have specialized anatomical and physiological properties by using a combination of whole-cell recordings and optogenetic stimulation of V1 axons in vitro. We discovered area-specific differences in the strength of recruitment of interneurons through feed-forward and recurrent pathways, as well as differences in cell-intrinsic properties and interneuron densities. These differences were most striking when comparing across medial and lateral areas, suggesting that these areas have distinct profiles for net excitability and integration of V1 inputs. Thus, cortical areas are not defined simply by the information they receive, but also by area-specific circuit properties that enable specialized filtering of these inputs.

Invariant Synapse Density and Neuronal Connectivity Scaling in Primate Neocortical Evolution

Synapses are involved in the communication of information from one neuron to another. However, a systematic analysis of synapse density in the neocortex from a diversity of species is lacking, limiting what can be understood about the evolution of this fundamental aspect of brain structure. To address this, we quantified synapse density in supragranular layers II–III and infragranular layers V–VI from primary visual cortex and inferior temporal cortex in a sample of 25 species of primates, including humans. We found that synapse densities were relatively constant across these levels of the cortical visual processing hierarchy and did not significantly differ with brain mass, varying by only 1.9-fold across species. We also found that neuron densities decreased in relation to brain enlargement. Consequently, these data show that the number of synapses per neuron significantly rises as a function of brain expansion in these neocortical areas of primates. Humans displayed the highest number of synapses per neuron, but these values were generally within expectations based on brain size. The metabolic and biophysical constraints that regulate uniformity of synapse density, therefore, likely underlie a key principle of neuronal connectivity scaling in primate neocortical evolution.

Mapping Short Association Fibers in the Early Cortical Visual Processing Stream Using In Vivo Diffusion Tractography

Short association fibers (U-fibers) connect proximal cortical areas and constitute the majority of white matter connections in the human brain. U-fibers play an important role in brain development, function, and pathology but are underrepresented in current descriptions of the human brain connectome, primarily due to methodological challenges in diffusion magnetic resonance imaging (dMRI) of these fibers. High spatial resolution and dedicated fiber and tractography models are required to reliably map the U-fibers. Moreover, limited quantitative knowledge of their geometry and distribution makes validation of U-fiber tractography challenging. Submillimeter resolution diffusion MRI—facilitated by a cutting-edge MRI scanner with 300 mT/m maximum gradient amplitude—was used to map U-fiber connectivity between primary and secondary visual cortical areas (V1 and V2, respectively) in vivo. V1 and V2 retinotopic maps were obtained using functional MRI at 7T. The mapped V1–V2 connectivity was retinotopically organized, demonstrating higher connectivity for retinotopically corresponding areas in V1 and V2 as expected. The results were highly reproducible, as demonstrated by repeated measurements in the same participants and by an independent replication group study. This study demonstrates a robust U-fiber connectivity mapping in vivo and is an important step toward construction of a more complete human brain connectome.

Dynamics of visual contextual interactions is altered in Parkinson’s disease

Over the last decades, psychophysical and electrophysiological studies in patients and animal models of Parkinson’s disease (PD), have consistently revealed a number of visual abnormalities. In particular, specific alterations of contrast sensitivity curves, electroretinogram (ERG), and visual evoked potentials (VEP), have been attributed to dopaminergic retinal depletion. However, fundamental mechanisms of cortical visual processing, such as normalization or “gain-control” computations, have not yet been examined in PD patients. Here we measured electrophysiological indices of gain control in both space (surround suppression) and time (sensory adaptation) in PD patients based on steady-state VEP (ssVEP). Compared to controls, patients exhibited a significantly higher initial ssVEP amplitude that quickly decayed over time, and greater relative suppression of ssVEP amplitude as a function of surrounding stimulus contrast. Meanwhile, EEG frequency spectra were broadly elevated in patients relative to controls. Thus, contrary to what might be expected given the reduced contrast sensitivity often reported in PD, visual neural responses are not weaker; rather, they are initially larger but undergo an exaggerated degree of spatial and temporal gain control and are embedded within a greater background noise level. We conclude that compensatory cortical mechanisms may play a role in determining dysfunctional center-surround interactions at the retinal level.

Higher order, multifeatural object encoding by the oculomotor system

Previous behavioral and physiological research has demonstrated that as the behavioral relevance of potential saccade goals increases, they elicit more competition during target selection processing as evidenced by increased saccade curvature and neural activity. However, these effects have only been demonstrated for lower order feature singletons, and it remains unclear whether more complicated featural differences between higher order objects also elicit vector modulation. Therefore, we measured human saccades curvature elicited by distractors bilaterally flanking a target during a visual search saccade task and systematically varied subsets of features shared between the two distractors and the target, referred to as objective similarity (OS). Our results demonstrate that saccades deviated away from the distractor highest in OS to the target and that there was a linear relationship between the magnitude of saccade deviation and the number of feature differences between the most similar distractor and the target. Furthermore, an analysis of curvature over the time course of the saccade demonstrated that curvature only occurred in the first 20–30 ms of the movement. Given the multifeatural complexity of the novel stimuli, these results suggest that saccadic target selection processing involves dynamically reweighting vector representations for movement planning to several possible targets based on their behavioral relevance. NEW & NOTEWORTHY We demonstrate that small featural differences between unfamiliar, higher order object representations modulate vector weights during saccadic target selection processing. Such effects have previously only been demonstrated for familiar, simple feature singletons (e.g., color) in which features characterize entire objects. The complexity and novelty of our stimuli suggest that the oculomotor system dynamically receives visual/cognitive information processed in the higher order representational networks of the cortical visual processing hierarchy and integrates this information for saccadic movement planning.

Measuring Early Cortical Visual Processing in the Clinic

We describe a mobile app that measures early cortical visual processing suitable for use in clinics. The app is called Component Extraction and Motion Integration Test (CEMIT). Observers are asked to respond to the direction of translating plaids that move in one of two very different directions. The plaids have been selected so that the plaid components move in one of the directions and the plaid pattern moves in the other direction. In addition to correctly responding to the pattern motion, observers demonstrate their ability to correctly extract the movement (and therefore the orientation) of the underlying components at specific spatial frequencies. We wanted to test CEMIT by seeing if we could replicate the broader tuning observed at low spatial frequencies for this type of plaid. Results from CEMIT were robust and successfully replicated this result for 50 typical observers. We envisage that it will be of use to researchers and clinicians by allowing them to investigate specific deficits at this fundamental level of cortical visual processing. CEMIT may also be used for screening purposes where visual information plays an important role, for example, air traffic controllers.