Motor performance and functional connectivity between the posterior cingulate cortex and supplementary motor cortex in bipolar and unipolar depression.

Although implicated in unsuccessful treatment, psychomotor deficits and their neurobiological underpinnings in bipolar (BD) and unipolar (UD) depression remain poorly investigated. Here, we hypothesized that motor performance deficits in depressed patients would relate to basal functional coupling of the hand primary motor cortex (M1) and the posterior cingulate cortex (PCC) with the supplementary motor area (SMA). We performed a longitudinal, naturalistic study in BD, UD and matched healthy controls comprising of two resting-state functional MRI measurements five weeks apart and accompanying assessments of motor performance using a finger tapping task (FTT). A subject-specific seed-based analysis describing functional connectivity between PCC-SMA as well as M1-SMA was conducted. The basal relationships with motor performance were investigated using linear regression models and all measures were compared across groups. Performance in FTT was impaired in BD in comparison to HC in both sessions. Behavioral performance across groups correlated significantly with resting state functional coupling of PCC-SMA, but not of M1-SMA regions. This relationship was partially reflected in a reduced PCC-SMA connectivity in BD vs HC in the second session. Exploratory evaluation of large-scale networks coupling (SMN-DMN) exhibited no correlation to motor performance. Our results shed new light on the association between the degree of disruption in the SMA-PCC anticorrelation and the level of motor impairment in BD.

Strategic deployment of feature-based attentional gain in primate visual cortex.

Attending to visual stimuli enhances the gain of those neurons in primate visual cortex that preferentially respond to the matching locations and features (on-target gain). Although this is well suited to enhance the neuronal representation of attended stimuli, it is nonoptimal under difficult discrimination conditions, as in the presence of similar distractors. In such cases, directing attention to neighboring neuronal populations (off-target gain) has been shown to be the most efficient strategy, but although such a strategic deployment of attention has been shown behaviorally, its underlying neural mechanisms are unknown. Here, we investigated how attention affects the population responses of neurons in the middle temporal (MT) visual area of rhesus monkeys to bidirectional movement inside the neurons' receptive field (RF). The monkeys were trained to focus their attention onto the fixation spot or to detect a direction or speed change in one of the motion directions (the "target"), ignoring the distractor motion. Population activity profiles were determined by systematically varying the patterns' directions while maintaining a constant angle between them. As expected, the response profiles show a peak for each of the 2 motion directions. Switching spatial attention from the fixation spot into the RF enhanced the peak representing the attended stimulus and suppressed the distractor representation. Importantly, the population data show a direction-dependent attentional modulation that does not peak at the target feature but rather along the slopes of the activity profile representing the target direction. Our results show that attentional gains are strategically deployed to optimize the discriminability of target stimuli, in line with an optimal gain mechanism proposed by Navalpakkam and Itti.

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.

TMS-induced neuronal plasticity enables targeted remodeling of visual cortical maps.

Transcranial magnetic stimulation (TMS) has become a popular clinical method to modify cortical processing. The events underlying TMS-induced functional changes remain, however, largely unknown because current noninvasive recording methods lack spatiotemporal resolution or are incompatible with the strong TMS-associated electrical field. In particular, an answer to the question of how the relatively unspecific nature of TMS stimulation leads to specific neuronal reorganization, as well as a detailed picture of TMS-triggered reorganization of functional brain modules, is missing. Here we used real-time optical imaging in an animal experimental setting to track, at submillimeter range, TMS-induced functional changes in visual feature maps over several square millimeters of the brain's surface. We show that high-frequency TMS creates a transient cortical state with increased excitability and increased response variability, which opens a time window for enhanced plasticity. Visual stimulation (i.e., 30 min of passive exposure) with a single orientation applied during this TMS-induced permissive period led to enlarged imprinting of the chosen orientation on the visual map across visual cortex. This reorganization was stable for hours and was characterized by a systematic shift in orientation preference toward the trained orientation. Thus, TMS can noninvasively trigger a targeted large-scale remodeling of fundamentally mature functional architecture in early sensory cortex.

Voltage-sensitive dye imaging of transcranial magnetic stimulation-induced intracortical dynamics.

Transcranial magnetic stimulation (TMS) is widely used in clinical interventions and basic neuroscience. Additionally, it has become a powerful tool to drive plastic changes in neuronal networks. However, highly resolved recordings of the immediate TMS effects have remained scarce, because existing recording techniques are limited in spatial or temporal resolution or are interfered with by the strong TMS-induced electric field. To circumvent these constraints, we performed optical imaging with voltage-sensitive dye (VSD) in an animal experimental setting using anaesthetized cats. The dye signals reflect gradual changes in the cells' membrane potential across several square millimeters of cortical tissue, thus enabling direct visualization of TMS-induced neuronal population dynamics. After application of a single TMS pulse across visual cortex, brief focal activation was immediately followed by synchronous suppression of a large pool of neurons. With consecutive magnetic pulses (10 Hz), widespread activity within this "basin of suppression" increased stepwise to suprathreshold levels and spontaneous activity was enhanced. Visual stimulation after repetitive TMS revealed long-term potentiation of evoked activity. Furthermore, loss of the "deceleration-acceleration" notch during the rising phase of the response, as a signature of fast intracortical inhibition detectable with VSD imaging, indicated weakened inhibition as an important driving force of increasing cortical excitability. In summary, our data show that high-frequency TMS changes the balance between excitation and inhibition in favor of an excitatory cortical state. VSD imaging may thus be a promising technique to trace TMS-induced changes in excitability and resulting plastic processes across cortical maps with high spatial and temporal resolutions.

Subject-specific whole-brain parcellations of nodes and boundaries are modulated differently under 10 Hz rTMS.

Repetitive transcranial magnetic stimulation (rTMS) has gained considerable importance in the treatment of neuropsychiatric disorders, including major depression. However, it is not yet understood how rTMS alters brain's functional connectivity. Here we report changes in functional connectivity captured by resting state functional magnetic resonance imaging (rsfMRI) within the first hour after 10 Hz rTMS. We apply subject-specific parcellation schemes to detect changes (1) in network nodes, where the strongest functional connectivity of regions is observed, and (2) in network boundaries, where functional transitions between regions occur. We use support vector machine (SVM), a widely used machine learning algorithm that is robust and effective, for the classification and characterization of time intervals of changes in node and boundary maps. Our results reveal that changes in connectivity at the boundaries are slower and more complex than in those observed in the nodes, but of similar magnitude according to accuracy confidence intervals. These results were strongest in the posterior cingulate cortex and precuneus. As network boundaries are indeed under-investigated in comparison to nodes in connectomics research, our results highlight their contribution to functional adjustments to rTMS.

Attention enhances stimulus representations in macaque visual cortex without affecting their signal-to-noise level.

The magnitude of the attentional modulation of neuronal responses in visual cortex varies with stimulus contrast. Whether the strength of these attentional influences is similarly dependent on other stimulus properties is unknown. Here we report the effect of spatial attention on responses in the medial-temporal area (MT) of macaque visual cortex to moving random dots pattern of various motion coherences, i.e. signal-to-noise ratios. Our data show that allocating spatial attention causes a gain change in MT neurons. The magnitude of this attentional modulation is independent of the attended stimulus' motion coherence, creating a multiplicative scaling of the neuron's coherence-response function. This is consistent with the characteristics of gain models of attentional modulation and suggests that attention strengthens the neuronal representation of behaviorally relevant visual stimuli relative to unattended stimuli, but without affecting their signal-to-noise ratios.

Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data.

Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We find that all models can be well-fitted, that the best model generally varies between neurons and that statistical comparisons between neuronal responses across different experimental conditions are affected quantitatively and qualitatively by specific model choices. As a robust alternative to an often arbitrary model selection, we introduce a model-free approach, in which features of interest are extracted directly from the measured response data without the need of fitting any model. In our attentional datasets, we demonstrate that data-driven methods provide descriptions of tuning curve features such as preferred stimulus direction or attentional gain modulations which are in agreement with fit-based approaches when a good fit exists. Furthermore, these methods naturally extend to the frequent cases of uncertain model selection. We show that model-free approaches can identify attentional modulation patterns, such as general alterations of the irregular shape of tuning curves, which cannot be captured by fitting stereotyped conventional models. Finally, by comparing datasets across different conditions, we demonstrate effects of attention that are cell- and even stimulus-specific. Based on these proofs-of-concept, we conclude that our data-driven methods can reliably extract relevant tuning information from neuronal recordings, including cells whose seemingly haphazard response curves defy conventional fitting approaches.

Neurons in Primate Visual Cortex Alternate between Responses to Multiple Stimuli in Their Receptive Field.

A fundamental question concerning representation of the visual world in our brain is how a cortical cell responds when presented with more than a single stimulus. We find supportive evidence that most cells presented with a pair of stimuli respond predominantly to one stimulus at a time, rather than a weighted average response. Traditionally, the firing rate is assumed to be a weighted average of the firing rates to the individual stimuli (response-averaging model) (Bundesen et al., 2005). Here, we also evaluate a probability-mixing model (Bundesen et al., 2005), where neurons temporally multiplex the responses to the individual stimuli. This provides a mechanism by which the representational identity of multiple stimuli in complex visual scenes can be maintained despite the large receptive fields in higher extrastriate visual cortex in primates. We compare the two models through analysis of data from single cells in the middle temporal visual area (MT) of rhesus monkeys when presented with two separate stimuli inside their receptive field with attention directed to one of the two stimuli or outside the receptive field. The spike trains were modeled by stochastic point processes, including memory effects of past spikes and attentional effects, and statistical model selection between the two models was performed by information theoretic measures as well as the predictive accuracy of the models. As an auxiliary measure, we also tested for uni- or multimodality in interspike interval distributions, and performed a correlation analysis of simultaneously recorded pairs of neurons, to evaluate population behavior.

Lateral interactions in the perception of flicker and in the physiology of the lateral geniculate nucleus.

The perception of flicker strength in a center stimulus can be affected by the presence of a surrounding stimulus. We correlated this effect with the interactions between centers and surrounds of the receptive fields (RFs) of neurons in the retino-geniculate pathways. The responses of cells in the lateral geniculate nucleus (LGN) of two New World monkey species, the common marmoset (Callithrix jacchus), and the owl monkey (Aotus azarae) were measured to two spatially non-overlapping sinusoidally modulating luminance stimuli of equal temporal frequency, one of which mainly stimulated the RF center, the other the RF surround. The relative temporal phase between the center and surround stimuli was varied. The response amplitude as a function of relative phase between the center and surround stimuli can be described by a simple model where the RF center and surround responses are vector-added. A minimal response was reached for stimuli in which the surround stimulus led the center stimulus, indicating that the RF surround response lagged the center response. The flicker strength in the center stimulus perceived by human observers was measured psychophysically. It was found that the perceived flicker strength could be described by the same function as was used for the cell data. There were qualitative similarities between the physiological and the psychophysical data, suggesting that the physiological basis of the psychophysically measured spatial interactions is present as early as the LGN. The data indicated the presence of a nonlinearity in center-surround interactions that is influenced by the stimulus contrast. The possible source of this nonlinearity was studied by comparing the center and the surround responses with those in which they were selectively stimulated.

Linking lateral interactions in flicker perception to lateral geniculate nucleus cell responses.

The perception of flicker strength in a circular stimulus can be changed by altering the relative temporal phase of a simultaneously flickering surrounding annulus: perceived flicker is weak when the two stimuli are modulated in-phase and strong when the two are modulated in counter-phase. Previously, we found that responses of single neurons in the monkey lateral geniculate nucleus (LGN) to such stimuli resemble the psychophysical data. On the basis of the resemblance in data, it was proposed that the physiological basis for the flicker perception may be present as proximal as the LGN. To strengthen this hypothesis, we simulated the response of an array of LGN neurons, the receptive fields (RFs) of which are covered by the stimulus. The simulations were based upon single-cell recordings in the LGN of anaesthetized marmosets (Callithrix jacchus) using the same stimuli as previously. The measurements were repeated for different spatial displacement between the stimulus and the RF. The responses depended upon the spatial displacement and the relative phase between centre and surround stimuli. The neuronal responses can be adequately described by a difference-of-Gaussians (DOG) model with a time delay in the RF surround. The model responses at different displacements can be considered to be identical to the output of an array of ideal and identical LGN cells with different RF locations. To be able to describe physiological and psychophysical data, obtained at different stimulus contrasts, it was necessary to consider previously described non-linear interactions between the RF centres and surrounds. We applied a spatial peak-to-trough detector with a subsequent saturation and threshold to simulate a simple cortical decision mechanism. The output of this peak-to-trough detector could adequately describe the psychophysical data.