Multiple neural spike train data analysis: state-of-the-art and future challenges
Multiple electrodes are now a standard tool in neuroscience research that make it possible
to study the simultaneous activity of several neurons in a given brain region or across …
to study the simultaneous activity of several neurons in a given brain region or across …
Statistical issues in the analysis of neuronal data
Analysis of data from neurophysiological investigations can be challenging. Particularly
when experiments involve dynamics of neuronal response, scientific inference can become …
when experiments involve dynamics of neuronal response, scientific inference can become …
Functional neuronal circuitry and oscillatory dynamics in human brain organoids
Human brain organoids replicate much of the cellular diversity and developmental anatomy
of the human brain. However, the physiology of neuronal circuits within organoids remains …
of the human brain. However, the physiology of neuronal circuits within organoids remains …
Partitioning neuronal variability
Responses of sensory neurons differ across repeated measurements. This variability is
usually treated as stochasticity arising within neurons or neural circuits. However, some …
usually treated as stochasticity arising within neurons or neural circuits. However, some …
A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects
Multiple factors simultaneously affect the spiking activity of individual neurons. Determining
the effects and relative importance of these factors is a challenging problem in …
the effects and relative importance of these factors is a challenging problem in …
The time-rescaling theorem and its application to neural spike train data analysis
Measuring agreement between a statistical model and a spike train data series, that is,
evaluating goodness of fit, is crucial for establishing the model's validity prior to using it to …
evaluating goodness of fit, is crucial for establishing the model's validity prior to using it to …
Estimating a state-space model from point process observations
AC Smith, EN Brown - Neural computation, 2003 - direct.mit.edu
A widely used signal processing paradigm is the state-space model. The state-space model
is defined by two equations: an observation equation that describes how the hidden state or …
is defined by two equations: an observation equation that describes how the hidden state or …
Dynamic analysis of neural encoding by point process adaptive filtering
Neural receptive fields are dynamic in that with experience, neurons change their spiking
responses to relevant stimuli. To understand how neural systems adapt the irrepresentations …
responses to relevant stimuli. To understand how neural systems adapt the irrepresentations …
A point-process model of human heartbeat intervals: new definitions of heart rate and heart rate variability
R Barbieri, EC Matten, ARA Alabi… - American Journal of …, 2005 - journals.physiology.org
Heart rate is a vital sign, whereas heart rate variability is an important quantitative measure
of cardiovascular regulation by the autonomic nervous system. Although the design of …
of cardiovascular regulation by the autonomic nervous system. Although the design of …
Relating neuronal firing patterns to functional differentiation of cerebral cortex
It has been empirically established that the cerebral cortical areas defined by Brodmann one
hundred years ago solely on the basis of cellular organization are closely correlated to their …
hundred years ago solely on the basis of cellular organization are closely correlated to their …