A prefrontal network model operating near steady and oscillatory states links spike desynchronization and synaptic deficits in schizophrenia.

Schizophrenia results in part from a failure of prefrontal networks but we lack full understanding of how disruptions at a synaptic level cause failures at the network level. This is a crucial gap in our understanding because it prevents us from discovering how genetic mutations and environmental risks that alter synaptic function cause prefrontal network to fail in schizophrenia. To address that question, we developed a recurrent spiking network model of prefrontal local circuits that can explain the link between NMDAR synaptic and 0-lag spike synchrony deficits we recently observed in a pharmacological monkey model of prefrontal network failure in schizophrenia. We analyze how the balance between AMPA and NMDA components of recurrent excitation and GABA inhibition in the network influence oscillatory spike synchrony to inform the biological data. We show that reducing recurrent NMDAR synaptic currents prevents the network from shifting from a steady to oscillatory state in response to extrinsic inputs such as might occur during behavior. These findings strongly parallel dynamic modulation of 0-lag spike synchrony we observed between neurons in monkey prefrontal cortex during behavior, as well as the suppression of this 0-lag spiking by administration of NMDAR antagonists. As such, our cortical network model provides a plausible mechanism explaining the link between NMDAR synaptic and 0-lag spike synchrony deficits observed in a pharmacological monkey model of prefrontal network failure in schizophrenia.

Schizophrenia is a long-term mental health condition that can cause a person to see, hear or believe things that are not real. Although researchers do not fully understand the causes of schizophrenia, it is known to disrupt synapses, which connect neurons in the brain to form circuits that carry out a specific function when activated. This disruption alters the pattern of activity among the neurons, distorting the way that information is processed and leading to symptoms. Development of schizophrenia is thought to be due to interactions between many factors, including genetic makeup, changes in how the brain matures during development, and environmental stress. Despite animal studies revealing how neural circuits can fail at the level of individual cells, it remains difficult to predict or understand the complex ways that this damage affects advanced brain functions. Previous research in monkeys showed that mimicking schizophrenia using a drug that blocks a particular type of synapse prevented neurons from coordinating their activity. However, this did not address how synaptic and cellular changes lead to disrupted neural circuits. To better understand this, Crowe et al. developed a computational model of neural circuits to study how they respond to synapse disruption. To replicate the brain, the model consisted of two types of neurons ­ those that activate connecting cells in response to received signals and those that suppress them. This model could replicate the complex network behavior that causes brain cells to respond to sensory inputs. Increasing the strength of inputs to the network caused it to switch from a state in which the cells fired independently to one where the cells fired at the same time. As was previously seen in monkeys, blocking a particular type of synapse thought to be involved in schizophrenia prevented the cells from coordinating their signaling. The findings suggest that schizophrenia-causing factors can reduce the ability of neurons to fire at the same instant. Disrupting this process could lead to weaker and fewer synapses forming during brain development or loss of synapses in adults. If that is the case, and scientists can understand how factors combine to trigger this process, the mechanism of coordinated activity failure revealed by the model could help identify treatments that prevent or reverse the synapse disruption seen in schizophrenia.

Mapping of the preferred direction in the motor cortex.

Directional tuning is a basic functional property of cell activity in the motor cortex. Previous work has indicated that cells with similar preferred directions are organized in columns perpendicular to the cortical surface. Here we show that these columns are organized in an orderly fashion in the tangential dimension on the cortical surface. Based on a large number of microelectrode penetrations and systematic exploration of the proximal arm area of the motor cortex while monkeys made free reaching 3D movements, it was estimated that (i) directional minicolumns are approximately 30 mum in width, (ii) minicolumns with similar preferred directions tend to occur in doublets or triplets, and (iii) such minicolumns tend to repeat every approximately 240 mum (estimated width of a column), with intermediate preferred directions represented in a gradient. These findings provide evidence for an orderly mapping of the preferred direction in the motor cortex.

Blocking NMDAR Disrupts Spike Timing and Decouples Monkey Prefrontal Circuits: Implications for Activity-Dependent Disconnection in Schizophrenia.

We employed multi-electrode array recording to evaluate the influence of NMDA receptors (NMDAR) on spike-timing dynamics in prefrontal networks of monkeys as they performed a cognitive control task measuring specific deficits in schizophrenia. Systemic, periodic administration of an NMDAR antagonist (phencyclidine) reduced the prevalence and strength of synchronous (0-lag) spike correlation in simultaneously recorded neuron pairs. We employed transfer entropy analysis to measure effective connectivity between prefrontal neurons at lags consistent with monosynaptic interactions and found that effective connectivity was persistently reduced following exposure to the NMDAR antagonist. These results suggest that a disruption of spike timing and effective connectivity might be interrelated factors in pathogenesis, supporting an activity-dependent disconnection theory of schizophrenia. In this theory, disruption of NMDAR synaptic function leads to dysregulated timing of action potentials in prefrontal networks, accelerating synaptic disconnection through a spike-timing-dependent mechanism.

Large-scale organization of preferred directions in the motor cortex. II. Analysis of local distributions.

The spatial arrangement of preferred directions (PDs) in the primary motor cortex has revealed evidence for columnar organization and short-range order. We investigated the large-scale properties of this arrangement. We recorded neural activity at sites on a grid covering a large region of the arm area of the motor cortex while monkeys performed a 3D reaching task. Sites were projected to the cortical surface along anatomically defined cortical columns and a PD was extracted from each site with directionally tuned activity. We analyzed the resulting 2D surface map of PDs. Consistent with previous studies, we found that any particular reaching direction was re-represented at many points across the recorded area. In particular, we determined that the median radius of a cortical region required to represent the full complement of reaching directions is at most 1 mm. We also found that for the majority of regions of this size, the distribution of PDs within them exhibits an enrichment for the representation of forward and backward reaching directions (see companion paper). Finally, we found that the error of a population vector estimate of reaching direction constructed from neural activity within these regions is small on average, but varies significantly across different sections of the motor cortex, with the highest levels of error sustained near the fundus of the central sulcus and lowest levels achieved near the crown. We interpret these findings in the context of two well-known features of motor cortex, that is, its highly distributed anatomical organization and its behaviorally dependent plasticity.

Large-scale organization of preferred directions in the motor cortex. I. Motor cortical hyperacuity for forward reaching.

We used statistical methods for spherical density estimation to evaluate the distribution of preferred directions of motor cortical cells recorded from monkeys making reaching movements in 3D space. We found that this distribution, although broad enough to represent the entire 3D continuum of reaching directions, exhibited an enrichment for reaching forward from the body and, to a lesser degree, for reaching backward toward the body. The distribution of preferred directions of cells in the motor cortex may have important implications for motor cortical function and for the decoding of arm trajectories from population activity.

A phenomenological theory of spatially structured local synaptic connectivity.

The structure of local synaptic circuits is the key to understanding cortical function and how neuronal functional modules such as cortical columns are formed. The central problem in deciphering cortical microcircuits is the quantification of synaptic connectivity between neuron pairs. I present a theoretical model that accounts for the axon and dendrite morphologies of pre- and postsynaptic cells and provides the average number of synaptic contacts formed between them as a function of their relative locations in three-dimensional space. An important aspect of the current approach is the representation of a complex structure of an axonal/dendritic arbor as a superposition of basic structures-synaptic clouds. Each cloud has three structural parameters that can be directly estimated from two-dimensional drawings of the underlying arbor. Using empirical data available in literature, I applied this theory to three morphologically different types of cell pairs. I found that, within a wide range of cell separations, the theory is in very good agreement with empirical data on (i) axonal-dendritic contacts of pyramidal cells and (ii) somatic synapses formed by the axons of inhibitory interneurons. Since for many types of neurons plane arborization drawings are available from literature, this theory can provide a practical means for quantitatively deriving local synaptic circuits based on the actual observed densities of specific types of neurons and their morphologies. It can also have significant implications for computational models of cortical networks by making it possible to wire up simulated neural networks in a realistic fashion.

Spatial reconstruction of trajectories of an array of recording microelectrodes.

We present a method for estimating the locations of sites visited by an array of microelectrodes. The method relies on visualization of tracks made by electrodes coated in a fluorescent dye. These tracks are used to estimate the parameters of a simple geometrical model that generates coordinates for each recording site. We describe several ways to measure the error of this procedure and present experimental results from recordings in the motor cortex of macaque monkeys that suggest that errors are of the order of 230 microm. We also introduce a coordinate transformation that takes into account the convoluted structure of the cortex near sulci to conveniently visualize recording site locations in a rectilinear representation. This method greatly extends the capabilities of microelectrodes for studying the three-dimensional structure of topographic maps in the cortex.

Logarithmic transformation for high-field BOLD fMRI data.

Parametric statistical analyses of BOLD fMRI data often assume that the data are normally distributed, the variance is independent of the mean, and the effects are additive. We evaluated the fulfilment of these conditions on BOLD fMRI data acquired at 4 T from the whole brain while 15 subjects fixated a spot, looked at a geometrical shape, and copied it using a joystick. We performed a detailed analysis of the data to assess (a) their frequency distribution (i.e. how close it was to a normal distribution), (b) the dependence of the standard deviation (SD) on the mean, and (c) the dependence of the response on the preceding baseline. The data showed a strong departure from normality (being skewed to the right and hyperkurtotic), a strong linear dependence of the SD on the mean, and a proportional response over the baseline. These results suggest the need for a logarithmic transformation. Indeed, the log transformation reduced the skewness and kurtosis of the distribution, stabilized the variance, and made the effect additive, i.e. independent of the baseline. We conclude that high-field BOLD fMRI data need to be log-transformed before parametric statistical analyses are applied.

Modular organization of directionally tuned cells in the motor cortex: is there a short-range order?

We investigated the presence of short-range order (<600 microm) in the directional properties of neurons in the motor cortex of the monkey. For that purpose, we developed a quantitative method for the detection of functional cortical modules and used it to examine such potential modules formed by directionally tuned cells. In the functional domain, we labeled each cell by its preferred direction (PD) vector in 3D movement space; in the spatial domain, we used the position of the tip of the recording microelectrode as the cell's coordinate. The images produced by this method represented two orthogonal dimensions in the cortex; one was parallel ("horizontal") and the other perpendicular ("vertical") to the cortical layers. The distribution of directionally tuned cells in these dimensions was nonuniform and highly structured. Specifically, cells with similar PDs tended to segregate into vertically oriented minicolumns 50-100 microm wide and at least 500 microm high. Such minicolumns aggregated across the horizontal dimension in a secondary structure of higher order. In this structure, minicolumns with similar PDs were approximately 200 microm apart and were interleaved with minicolumns representing nearly orthogonal PDs; in addition, nonoverlapping columns representing nearly opposite PDs were approximately 350 microm apart.

Cerebellar activation during copying geometrical shapes.

We studied functional MRI activation in the cerebellum during copying 9 geometrical shapes (equilateral triangle, isosceles triangle, square, diamond, vertical trapezoid, pentagon, hexagon, circle, and vertical lemniscate). Twenty subjects were imaged during 3 consecutive 45-s periods (rest, visual presentation, and copying). First, there was a positive relation between cerebellar activation and the peak speed of individual movements. This effect was strongest in the lateral and posterior ipsilateral cerebellum but it was also present in the paramedian zones of both cerebellar hemispheres and in the vermis. A finer grain analysis of the relations between the time course of the blood oxygenation level-dependent activation and movement parameters revealed a significant relation to hand position and speed but not to acceleration. Second, there was a significant relation between the intensity of voxel activation during visual presentation and the speed of the upcoming movement. The spatial distribution of these voxels was very similar to that of the voxels activated during copying, indicating that the cerebellum might be involved in motor rehearsal, in addition to its role during movement execution. Finally, a factor analysis of the intensity of activated voxels in the ipsilateral cerebellum during copying (adjusted for the speed effect) extracted 3 shape factors. Factor 1 reflected "roundness," factor 2 "upward pointing," and factor 3 "pointing (up or down) and elongation." These results link cerebellar activation to more global, spatial aspects of copying.