Jorge Mariño

Invariant computations in local cortical networks with balanced excitation and inhibition

Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

TONIC AND BURSTING ACTIVITY IN THE CUNEATE NUCLEUS OF THE CHLORALOSE-ANESTHETIZED CAT

Whole-cell recordings were obtained from cuneate neurons in anesthetized, paralysed cats. Stimulation of the contralateral medial lemniscus permitted us to separate projection cells from presumed interneurons. Pericruciate motor cortex electrical stimulation inhibited postsynaptically all the projection cells (n=57) and excited all the presumed interneurons (n=29). The cuneothalamic cells showed an oscillatory and a tonic mode of activity. Membrane depolarization and primary afferent stimulation converted the oscillatory to the tonic mode. Hyperpolarizing current steps applied to projection neurons induced a depolarizing sag and bursts of conventional spikes in current-clamp records. This indicates the probable existence of low-threshold and hyperpolarization-activated inward currents. Also, the hyperpolarization induced on projection cells by motor cortex stimulation deinactivated a low-threshold conductance that led to bursting activity. The presumed cuneate interneurons had larger and more proximally located peripheral receptive fields than the cuneothalamic cells. Finally, experiments specifically designed to test whether motor cortex-induced presynaptic inhibition could be postsynaptically detected gave negative results. These results demonstrate, for the first time, that the cuneothalamic cells possess both bursting and tonic firing modes, and that membrane depolarization, whether produced by injection of positive current or by primary afferent stimulation, converts the oscillatory into the tonic mode.

Effects on EEG of Low (1Hz) and High (15Hz) Frequency Repetitive Transcranial Magnetic Stimulation of the Visual Cortex: A Study in the Anesthetized Cat

Here we confirm our earlier findings that showed 1Hz rTMS over the primary visual cortex of the anesthetized cat, known to cause inhibition of the cortex, induces an increase in power in the slow, delta band of the EEG. We also demonstrate that these inhibitory effects of 1Hz rTMS may be measured as changes of spatiotemporal receptive field pa- rameters at the single cell level. We extend these observations to show that higher frequency stimulation of the cortex at 15Hz has the opposite effect of decreasing delta activity, which was also accompanied by significant increases in theta, alpha and beta bands. This highly reproducible EEG change may be useful as a simple marker to predict inhibitory or ex- citatory rTMS effects known to be dependent upon stimulation frequency.

Functional two-way analysis of variance and bootstrap methods for neural synchrony analysis

BackgroundPairwise association between neurons is a key feature in understanding neural coding. Statistical neuroscience provides tools to estimate and assess these associations. In the mammalian brain, activating ascending pathways arise from neuronal nuclei located at the brainstem and at the basal forebrain that regulate the transition between sleep and awake neuronal firing modes in extensive regions of the cerebral cortex, including the primary visual cortex, where neurons are known to be selective for the orientation of a given stimulus. In this paper, the estimation of neural synchrony as a function of time is studied in data obtained from anesthetized cats. A functional data analysis of variance model is proposed. Bootstrap statistical tests are introduced in this context; they are useful tools for the study of differences in synchrony strength regarding 1) transition between different states (anesthesia and awake), and 2) affinity given by orientation selectivity.ResultsAn analysis of variance model for functional data is proposed for neural synchrony curves, estimated with a cross-correlation based method. Dependence arising from the experimental setting needs to be accounted for. Bootstrap tests allow the identification of differences between experimental conditions (modes of activity) and between pairs of neurons formed by cells with different affinities given by their preferred orientations. In our test case, interactions between experimental conditions and preferred orientations are not statistically significant.ConclusionsThe results reflect the effect of different experimental conditions, as well as the affinity regarding orientation selectivity in neural synchrony and, therefore, in neural coding. A cross-correlation based method is proposed that works well under low firing activity. Functional data statistical tools produce results that are useful in this context. Dependence is shown to be necessary to account for, and bootstrap tests are an appropriate method with which to do so.

Cross nearest-spike interval based method to measure synchrony dynamics

A new synchrony index for neural activity is defined in this paper. The method is able to measure synchrony dynamics in low firing rate scenarios. It is based on the computation of the time intervals between nearest spikes of two given spike trains. Generalized additive models are proposed for the synchrony profiles obtained by this method. Two hypothesis tests are proposed to assess for differences in the level of synchronization in a real data example. Bootstrap methods are used to calibrate the distribution of the tests. Also, the expected synchrony due to chance is computed analytically and by simulation to assess for actual synchronization.

Cortical Modulation of the Transient Visual Response at Thalamic Level: A TMS Study

The transient visual response of feline dorsal lateral geniculate nucleus (dLGN) cells was studied under control conditions and during the application of repetitive transcranial magnetic stimulation at 1 Hz (rTMS@1Hz) on the primary visual cortex (V1). The results show that rTMS@1Hz modulates the firing mode of Y cells, inducing an increase in burst spikes and a decrease in tonic firing. On the other hand, rTMS@1Hz modifies the spatiotemporal characteristics of receptive fields of X cells, inducing a delay and a decrease of the peak response, and a change of the surround/center amplitude ratio of RF profiles. These results indicate that V1 controls the activity of the visual thalamus in a different way in the X and Y pathways, and that this feedback control is consistent with functional roles associated with each cell type.

Bootstrap testing for cross-correlation under low firing activity

A new cross-correlation synchrony index for neural activity is proposed. The index is based on the integration of the kernel estimation of the cross-correlation function. It is used to test for the dynamic synchronization levels of spontaneous neural activity under two induced brain states: sleep-like and awake-like. Two bootstrap resampling plans are proposed to approximate the distribution of the test statistics. The results of the first bootstrap method indicate that it is useful to discern significant differences in the synchronization dynamics of brain states characterized by a neural activity with low firing rate. The second bootstrap method is useful to unveil subtle differences in the synchronization levels of the awake-like state, depending on the activation pathway.

Spectroscopic measurement of cortical nitric oxide release induced by ascending activation

The transition from sleep to the awake state is regulated by the activation of subcortical nuclei of the brainstem (BS) and basal forebrain (BF), releasing acetylcholine and glutamate throughout the cortex and inducing a tonic state of neural activity. It has been suggested that such activation is also mediated by the massive and diffuse cortical release of nitric oxide (NO). In this work we have combined the spectroscopic measurement of NO levels in the somatosensory cortex of the cat through its marker methemoglobin, as well as two other hemodynamic markers (oxyhemoglobin--oxyHb--and deoxyhemoglobin--deoxyHb), together with the electrical stimulation of BS and BF--to induce an experimental transition from a sleep-like state to an awake-like mode. The results show an increase of NO levels either after BS or BF activation. The response induced by BS stimulation was biphasic in the three studied markers, and lasted for up to 30s. The changes induced by BF were monophasic lasting for up to 20s. The systemic blockade of NO production abolished the observed responses to BS whereas responses to BF stimulation were much less affected. These results indicate a crucial role for NO in the neuronal activation induced by the ascending systems.

Autocorrelation Measures and Independence Tests in Spike Trains

In the nervous system, neurons convey information by means of electric pulses called action potentials or spikes. The information is encoded in sequences of these pulses, called spike trains. In neurophysiological experiments, spike trains are recorded and analyzed statistically. Time intervals between action potentials is the key feature of spike trains.

Sleep and wakefulness in the cuneate nucleus: a computational study

The minimum-variance theory [12] was proposed to account for the eye and arm movement. However, we point out here that i) the input signals used in the the simulations are not Poisson processes; ii) when the input signal is a Poisson process, the solution of the minimumvariance is degenerate.