Gabrielle Gutierrez

Barnard College · Neuroscience and Behavior

Adaptation is a key component of efficient coding in sensory neurons. However, it remains unclear how neurons can provide a stable representation of external stimuli given their history-dependent responses. Here we show that a stable representation is maintained if efficiency is optimized by a population of neurons rather than by neurons individual...

The circadian clock orchestrates daily changes in physiology and behavior to ensure internal temporal order and optimal timing across the day. In animals, a central brain clock coordinates circadian rhythms throughout the body and is characterized by a remarkable robustness that depends on synaptic connections between constituent neurons. The clock...

The circadian clock orchestrates daily changes in physiology and behavior to ensure internal temporal order and optimal timing across the day. In animals, a central brain clock orchestrates circadian rhythms throughout the body and is characterized by a remarkable resilience that depends on synaptic connections between constituent neurons. The cloc...

Significance Computation in neural circuits relies on a common set of motifs, including divergence of common inputs to parallel pathways, convergence of multiple inputs to a single neuron, and nonlinearities that select some signals over others. Convergence and circuit nonlinearities, considered separately, can lead to a loss of information about i...

Neural circuits are structured with layers of converging and diverging connectivity, and selectivity-inducing nonlinearities at neurons and synapses. These components have the potential to hamper an accurate encoding of the circuit inputs. Past computational studies have optimized the nonlinearities of single neurons, or connection weights in netwo...

Adaptation is a key component of efficient coding in single neurons. However, it is unclear how a population of adapting neurons manage to accurately and stably encode their inputs. We start with an efficient coding framework and show that realistic spike-frequency adaptation emerges as a mechanism that enables a neural population to solve a global...

Electrical coupling in circuits can produce non-intuitive circuit dynamics, as seen in both experimental work from the crustacean stomatogastric ganglion and in computational models inspired by the connectivity in this preparation. Ambiguities in interpreting the results of electrophysiological recordings can arise if sets of pre- or postsynaptic n...

Cover Figure Neuromodulation of a single neuron in a circuit can either have little to no effect on the output of the circuit, or it can change the pattern of activity within that circuit. This is dependent on the synaptic parameters given the same circuit architecture, thus illustrating the insufficiency of the connectome alone for determining ci...

Rectifying electrical synapses are commonplace, but surprisingly little is known about how rectification alters the dynamics of neuronal networks. In this study, we use computational models to investigate how rectifying electrical synapses change the behavior of a small neuronal network that exhibits complex rhythmic output patterns. We begin with...

Multivariate goodness-of-fit analysis for the point process model increases confidence of the inference. A, Observed spike train and instantaneous firing rate estimates. Spike trains (top) and estimated firing rates are plotted for the first 800 ms of recordings. Outside of the bursts, the model assigns a zero firing probability to each time bin. P...

A linear rate model using the Granger causality criterion to define coupling does not accurately reproduce the known physiological connectivity for a wide range of parameter choices. A, Results of linear Granger causality analysis for varying amounts of data used for fitting. For comparison, previous analysis [29] used 5 s. The physiologically abse...

Results obtained from the point process model are robust to changes of parameters. A, Model selection for the maximal lag of self-coupling filters. To determine the time scale for the self-history kernels, models using only self-coupling terms were fitted to the spike trains and the model with an optimal BIC (Bayesian Information Criterion) was cho...

Goodness-of-fit analysis for the linear rate model can reveal its inadequacy. A, Comparison of original and fitted firing rates. The spike trains are smoothed with a half-Gaussian kernel of fixed bandwidth to obtain a smooth estimate of the firing rate (top). The fitted signals of the linear rate models (middle) and the residuals (bottom), the diff...

Additional methods. We present detailed information about methods on evaluating goodness-of-fit for point process models and linear rate models as well as how to quantify the uncertainty in the coupling strength estimates. (PDF)

The present study aims to further our understanding of electrical synapses by exploring their rectification in a neuronal circuit model. We investigate how rectification affects the functional output of a 5-cell, pattern-generating, model network and its sensitivity to synaptic modulation.

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have bee...

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patte...

Background / Purpose: We investigated the signal propagation properties of a small neuronal network of approximately 23 motor neurons with sinusoidal current injections of various frequencies into a single cell. We also investigated whether the chemical inhibitory synapses and electrical gap junctions had distinct contributions to the signal prop...

Background / Purpose: We explored the signal propagation properties of the stomatogastric ganglion of the Jonah crab, as a function of 3 different sinusoidal current frequencies injected into one cell in the small neuronal network of approximately 23 motor neurons. We investigated the contribution of electrical synapses to this signal propagation...

Understanding circuit function would be greatly facilitated by methods that allow the simultaneous estimation of the functional strengths of all of the synapses in the network during ongoing network activity. Towards that end, we used Granger causality analysis on electrical recordings from the pyloric network of the crab Cancer borealis, a small r...

The stomatogastric ganglion (STG) is an excellent model for studying cellular and network interactions because it contains a relatively small number of cells (approximately 25 in C. borealis) which are well characterized. The cells in the STG exhibit a broad range of outputs and are responsible for the motor actions of the stomach. The stomach cont...