Frequency modulation of cortical rhythmicity governs behavioral variability, excitability and synchrony of neurons in the visual cortex.

Research in cognitive neuroscience has renewed the idea that brain oscillations are a core organization implicated in fundamental brain functions. Growing evidence reveals that the characteristic features of these oscillations, including power, phase and frequency, are highly non-stationary, fluctuating alongside alternations in sensation, cognition and behavior. However, there is little consensus on the functional implications of the instantaneous frequency variation in cortical excitability and concomitant behavior. Here, we capitalized on intracortical electrophysiology in the macaque monkey's visual area MT performing a visuospatial discrimination task with visual cues. We observed that the instantaneous frequency of the theta-alpha oscillations (4-13 Hz) is modulated among specific neurons whose RFs overlap with the cued stimulus location. Interestingly, we found that such frequency modulation is causally correlated with MT excitability at both scales of individual and ensemble of neurons. Moreover, studying the functional relevance of frequency variations indicated that the average theta-alpha frequencies foreshadow the monkey's reaction time. Our results also revealed that the neural synchronization strength alters with the average frequency shift in theta-alpha oscillations, suggesting frequency modulation is critical for mutually adjusting MTs' rhythms. Overall, our findings propose that theta-alpha frequency variations modulate MT's excitability, regulate mutual neurons' rhythmicity and indicate variability in behavior.

Decoding Adaptive Visuomotor Behavior Mediated by Non-linear Phase Coupling in Macaque Area MT.

The idea that a flexible behavior relies on synchronous neural activity within intra- and inter-associated cortical areas has been a matter of intense research in human and animal neuroscience. The neurophysiological mechanisms underlying this behavioral correlate of the synchronous activity are still unknown. It has been suggested that the strength of neural synchrony at the level of population is an important neural code to guide an efficient transformation of the sensory input into the behavioral action. In this study, we have examined the non-linear synchronization between neural ensembles in area MT of the macaque visual cortex by employing a non-linear cross-frequency coupling technique, namely bicoherence. We trained a macaque monkey to detect a brief change in the cued stimulus during a visuomotor detection task. The results show that the non-linear phase synchronization in the high-gamma frequency band (100-250 Hz) predicts the animal's reaction time. The strength of non-linear phase synchronization is selective to the target stimulus location. In addition, the non-linearity characteristics of neural synchronization are selectively modulated when the monkey covertly attends to the stimulus inside the neuron's receptive field. This additional evidence indicates that non-linear neuronal synchronization may be affected by a cognitive function like spatial attention. Our neural and behavioral observations reflect that two crucial processes may be involved in processing of visuomotor information in area MT: (I) a non-linear cortical process (measured by the bicoherence) and (II) a linear process (measured by the spectral power).

Routing information flow by separate neural synchrony frequencies allows for "functionally labeled lines" in higher primate cortex.

Efficient transfer of sensory information to higher (motor or associative) areas in primate visual cortical areas is crucial for transforming sensory input into behavioral actions. Dynamically increasing the level of coordination between single neurons has been suggested as an important contributor to this efficiency. We propose that differences between the functional coordination in different visual pathways might be used to unambiguously identify the source of input to the higher areas, ensuring a proper routing of the information flow. Here we determined the level of coordination between neurons in area MT in macaque visual cortex in a visual attention task via the strength of synchronization between the neurons' spike timing relative to the phase of oscillatory activities in local field potentials. In contrast to reports on the ventral visual pathway, we observed the synchrony of spikes only in the range of high gamma (180 to 220 Hz), rather than gamma (40 to 70 Hz) (as reported previously) to predict the animal's reaction speed. This supports a mechanistic role of the phase of high-gamma oscillatory activity in dynamically modulating the efficiency of neuronal information transfer. In addition, for inputs to higher cortical areas converging from the dorsal and ventral pathway, the distinct frequency bands of these inputs can be leveraged to preserve the identity of the input source. In this way source-specific oscillatory activity in primate cortex can serve to establish and maintain "functionally labeled lines" for dynamically adjusting cortical information transfer and multiplexing converging sensory signals.

Neural Activity Predicts Reaction in Primates Long Before a Behavioral Response.

How neural activity is linked to behavior is a critical question in neural engineering and cognitive neurosciences. It is crucial to predict behavior as early as possible, to plan a machine response in real-time brain computer interactions. However, previous studies have studied the neural readout of behavior only within a short time before the action is performed. This leaves unclear, if the neural activity long before a decision could predict the upcoming behavior. By recording extracellular neural activities from the visual cortex of behaving rhesus monkeys, we show that: (1) both, local field potentials (LFPs) and the rate of neural spikes long before (>2 s) a monkey responds to a change, foretell its behavioral performance in a spatially selective manner; (2) LFPs, the more accessible component of extracellular activity, are a stronger predictor of behavior; and (3) LFP amplitude is positively correlated while spiking activity is negatively correlated with behavioral reaction time (RT). These results suggest that field potentials could be used to predict behavior way before it is performed, an observation that could potentially be useful for brain computer interface applications, and that they contribute to the sensory neural circuit's speed in information processing.

FoCA: A new framework of coupled geometric active contours for segmentation of 3D cardiac magnetic resonance images.

In this paper, a new framework of coupled active contours (FoCA) is proposed for segmentation of the left ventricle myocardium, in cardiac magnetic resonance (CMR) images, without primary learning and user-driven segmentation. Primarily, we suggest a pair of coupled geometric active contours (GACs) for segmentation of the endo- and epicardial boundaries of the left ventricle in every CMR slice. The energy functional of each active contour includes the edge and shape terms of the STACS energy functional, regulator term of the local binary fitting (LBF), and new region and coupling terms. Two new patch-based region terms, inspired by LBF and piecewise model, are proposed to effectively handle intensity inhomogeneity of CMR images. Furthermore, a coupling energy term is added to the epicardial energy functional to avoid intersection with the endocardial curve. For 3D implementation, every 2D active contour in each slice is effectively jointed to the corresponding curves in the previous and next slices (of the same volume) by using a new coupling energy term, obtained by extending the 2D length-shortening regulator. Also, the initial contour and algorithm parameters are automatically regulated. Finally, 3D+t implementation is performed by using the sequential initialization method. Experimental results demonstrated that the proposed method provided superior solution quality compared to a large number of counterpart algorithms by using two well-known frequently-used databases.