Ultra-slow fluctuations are a hallmark of spontaneous cortical activity. We examine the hypothesis that these dynamics arise from recurrent neuronal networks operating near a phase-transition point, a state marked by "critical slowing down". In such networks, a subtle shift toward criticality should selectively amplify slow fluctuations, providing a lever that can switch the cortex from quiet rest into self-generated behavior. Using a simple random recurrent network, we reproduce this amplification effect. The resulting spectra closely match intracranial electroencephalography from human visual cortex recorded during rest and during category-specific visual free recall. In particular, the model captures the experimentally observed enhancement of slow fluctuations during recall. These simulations reveal a parsimonious mechanism that explains spontaneous ultra-slow activity and enables rapid transitions between spontaneous states, suggesting that dynamic tuning toward criticality may be a general strategy by which cortical networks enter a generative mode.

We have developed Brain-Voyant, an efficient general-purpose machine learning tool for real-time functional magnetic resonance imaging classification using whole-brain data, which can be used to explore novel brain-computer interface paradigms or advanced neurofeedback protocols. We have created a convenient and configurable front-end tool that receives fMRI-based multi-voxel raw brain data as input. Our tool processes, analyses, classifies and transfers the classification to an external object such as a virtual avatar or a humanoid robot in real-time. Our tool is focused on minimizing delay time, and to that end, it employs a method that is based on examining in advance the voxels that have been found to be task-relevant in the machine learning model training phase. The tool's code base was designed to be easily extended to support additional feature reduction, normalization and classification algorithms. This tool was used in several published studies using motor execution, motor imagery, and visual category classification in cue-based and free-choice brain-computer interface experiments, with both healthy and amputated subjects. This tool is not limited by number of classes, is not limited to predefined regions of interest, and classifier instances can run in parallel to combine multiple classification tasks in real time. Finally, our tool is able use the slow peaking blood-oxygen-level dependent signal to classify our subjects' intention during the two-second window TR. We release this tool as open-source for non-commercial usage.

The maximization of diversity of neuronal response properties has been recently suggested as an organizing principle for the formation of such prominent features of the functional architecture of the brain as the corti(cid:173) cal columns and the associated patchy projection patterns (Malach, 1994). We show that (1) maximal diversity is attained when the ratio of dendritic and axonal arbor sizes is equal to one, as found in many cortical areas and across species (Lund et al., 1993; Malach, 1994), and (2) that maxi(cid:173) mization of diversity leads to better performance in systems of receptive fields implementing steerable/shiftable filters, and in matching spatially distributed signals, a problem that arises in many high-level visual tasks. 1 Anatomical substrate for sampling diversity A fundamental feature of cortical architecture is its columnar organization, mani(cid:173) fested in the tendency of neurons with similar properties to be organized in columns that run perpendicular to the cortical surface. This organization of the cortex was ini(cid:173) tially discovered by physiological experiments (Mouncastle, 1957; Hubel and Wiesel, 1962), and subsequently confirmed with the demonstration of histologically defined columns. Tracing experiments have shown that axonal projections throughout the cerebral cortex tend to be organized in vertically aligned clusters or patches. In par(cid:173) ticular, intrinsic horizontal connections linking neighboring cortical sites, which may extend up to 2 - 3 mm, have a striking tendency to arborize selectively in preferred sites, forming distinct axonal patches 200 - 300 J.lm in diameter. Recently, it has been observed that the size of these patches matches closely the average diameter of individual dendritic arbors of upper-layer pyramidal cells 118 Kalanit Grill Spector, Shimon Edelman, Rafael Malach