The most insightful and direct access to non-conscious perception of visual signals is provided by studies of patients with lesions to the primary visual cortex (V1), resulting in a phenomenon called Blindsight. In this study, we implemented a Dynamic Functional Connectivity (DFC) analysis, to look at the brain dynamics and their relationship to Blindsight functions. Moreover, we evaluated the Effective Connectivity (EC) of each dynamical state through a whole brain modeling approach, in order to assess local differences in the brain functional structure of Blindsight patients.

Our DFC analysis involved 16 patients with right V1 lesions and 17 healthy subjects (HC). To assess the residual visual ability of the lesioned patients and categorize them into Blindsight positive (B+) and Blindsight negative (B-) we employed a behavioral task. Through a DFC analysis we defined a set of metastable states of brain dynamics. Then, we characterized how these attractors differ between the three groups, studying their dynamics and topological properties and evaluating their EC.

Based on clustering analysis of brain dynamics we found 4 metastable states. From a dynamical point of view, B+ show a higher permanence in the state related to the Default Mode Network (DMN). For what concerns B-, they exhibit a more probable self-transition within the somatomotor state. Looking at the topological properties of each state, we found an enhanced inter-hemispheric connectivity within the DMN state for B+. Moreover, looking at the integration of the information within the networks represented by each dynamical state, we observed an enhanced integration capability for B+ in the Global Signal (GS) state, i.e., a state of high synchronization of the activity throughout the brain. Thanks to the evaluation of the EC within each state, we observed an enhanced connectivity of subcortical structures, in particular contro-lesional Superior Colliculus and Lateral Geniculate Nucleus, with the somatomotor network, confirming the crucial role of subcortical structures in integrating visual information throughout the brain in Blindsight patients.

During perceptual decision-making, sensory information is transformed into decisions through the recruitment of specific neural ensembles that represent the subsequent choice. Previous studies in mice highlight the role of the Anterolateral Motor cortex (ALM), an area showing a significant proportion of neurons selectively encoding the upcoming choice (choice-ensembles) and whose photo-suppression causes pronounced deficits in choice performance (Guo et al. 2014; Pinto et al 2022). Moreover, modeling work has proposed that ALM choice-ensembles operate in a winner-take-all regime implying that one and only one ensemble is active during the choice maintenance period (Inagaki et al 2019). 

 To characterize the dynamics of ALM ensembles involved in choice selection and maintenance, we developed a multiple-choice delayed-response task (nDRT) for freely moving mice, where a brief stimulus is presented at one of three possible locations on a touchscreen. Animals had to retain the information during a short variable delay (~1s), after which they must respond by poking at the remembered stimulus location. We found that errors increased as a function of delay, indicating that mice made memory maintenance errors. In addition, we found a consistent dependence on previous responses (i.e. win-stay-lose-switch pattern) that remained unaffected by delay. Pharmacological ALM inactivation using GABA receptor agonists resulted in a decrease in choice accuracy, confirming the involvement of the area in the task.

We then aimed to characterize the interaction between ALM neural ensembles representing choice. We used a c-fos-driven tagging method (TRAP2 system) for the permanent expression of channelrhodopsin in ALM choice-ensembles. We TRAPed a neural ensemble specific to one choice by performing a behavioral session with a single choice. In subsequent sessions, photoactivation of the TRAPed ensemble did not bias task behavior towards the labeled choice. Instead, when stimulating at 5Hz, but not at 20Hz, it specifically impaired the accuracy for the labeled choice. These results suggest that the photostimulation of a specific choice ensemble in ALM does not interfere with the activation of other choice ensembles, but rather has a frequency-dependent choice-specific deleterious effect. Our findings provide important constraints on the network dynamics governing frontal cortex circuits during choice selection and maintenance.