wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our model demonstrates that deep learning can be achieved within a biologically feasible framework using segregated dendritic compartments  , which may help to explain the anatomy of neocortical pyramidal neurons.
Revised:  Our model demonstrates that deep learning can be achieved using segregated dendritic compartments , which may help to explain the anatomy of neocortical pyramidal neurons.
Edit intent: clarity
Original:  Our model demonstrates that deep learning can be achieved within a biologically feasible framework using segregated dendritic compartments  , which may help to explain the anatomy of neocortical pyramidal neurons.
Revised:  Our model demonstrates that deep learning can be achieved within a biologically feasible framework using segregated dendritic compartments , which may help to explain the dendritic morphology of neocortical pyramidal neurons.
Edit intent: clarity
Original:  Here, we show that deep learning can be achieved by moving away from point neuron models and towards multi-compartment neurons  . Like neocortical pyramidal neurons, neurons in our model receive feedforward sensory information and higher-order feedback in electrotonically segregated compartments.
Revised:  Here, we show that a deep learning algorithm that utilizes multi-compartment neurons . Like neocortical pyramidal neurons, neurons in our model receive feedforward sensory information and higher-order feedback in electrotonically segregated compartments.
Edit intent: clarity
Original:  Here, we show that deep learning can be achieved by moving away from point neuron models and towards multi-compartment neurons  . Like neocortical pyramidal neurons, neurons in our model receive feedforward sensory information and higher-order feedback in electrotonically segregated compartments.
Revised:  Here, we show that deep learning can be achieved by moving away from point neuron models and towards multi-compartment neurons . Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments.
Edit intent: clarity
Original:  Thanks to this segregation, the network can calculate local synaptic weight updates that allow it to categorize images from the MNIST data-set with good accuracy.
Revised:  Thanks to this segregation, the neurons in different layers of the network can coordinate synaptic weight updates that allow it to categorize images from the MNIST data-set with good accuracy.
Edit intent: clarity
Original:  Thanks to this segregation, the network can calculate local synaptic weight updates that allow it to categorize images from the MNIST data-set with good accuracy.
Revised:  Thanks to this segregation, the network can calculate local synaptic weight updates . As a result, the network can learn to categorize images from the MNIST data-set with good accuracy.
Edit intent: clarity
Original:  We show that our learning algorithm can take advantage of multilayer architectures to identify abstract categories---the hallmark of deep learning.
Revised:  We show that our algorithm takes advantage of multilayer architectures to identify abstract categories---the hallmark of deep learning.
Edit intent: clarity
Original:  We show that our learning algorithm can take advantage of multilayer architectures to identify abstract categories---the hallmark of deep learning.
Revised:  We show that our learning algorithm can take advantage of multilayer architectures to identify useful representations---the hallmark of deep learning.
Edit intent: clarity
Original:  This work demonstrates that deep learning can be achieved using segregated dendritic compartments for feedforward and feedback information , which may help to explain the dendritic morphology of neocortical pyramidal neurons.
Revised:  This work demonstrates that deep learning can be achieved using segregated dendritic compartments , which may help to explain the dendritic morphology of neocortical pyramidal neurons.
Edit intent: clarity
Original: Subspace learning and matrix factorization problems have a great many applications in science and engineering, and efficient algorithms are critical as dataset sizes continue to grow.
Revised: Subspace learning and matrix factorization problems have great many applications in science and engineering, and efficient algorithms are critical as dataset sizes continue to grow.
Edit intent: fluency
Original: Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients of different waveforms in response to stimulation.
Revised: Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation.
Edit intent: clarity
Original:   These transients have long been considered important for mapping excitability levels in the epileptic brain , but their dynamic mechanism is still not well-understood .
Revised:  These transients have long been considered important for the mapping of the excitability levels in the epileptic brain , but their dynamic mechanism is still not well-understood .
Edit intent: fluency
Original:   These transients have long been considered important for mapping excitability levels in the epileptic brain , but their dynamic mechanism is still not well-understood .
Revised:  These transients have long been considered important for mapping excitability levels in the epileptic brain but their dynamic mechanism is still not well-understood .
Edit intent: fluency
Original:   These transients have long been considered important for mapping excitability levels in the epileptic brain , but their dynamic mechanism is still not well-understood .
Revised:  These transients have long been considered important for mapping excitability levels in the epileptic brain , but their dynamic mechanism is still not well understood .
Edit intent: fluency
Original:  This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and a background state.
Revised:  This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state.
Edit intent: fluency
Original:  We analyse the state space geometry of the bistable and the excitable state , and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point.
Revised:  We analyse the state space geometry of the bistable and excitable states , and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point.
Edit intent: fluency
Original:  This area  allows trajectories to dwell in it for before escaping to the stable steady state, thus creating rhythmic transients.
Revised:  This area essentially allows trajectories to dwell in it for before escaping to the stable steady state, thus creating rhythmic transients.
Edit intent: clarity
Original:  This area  allows trajectories to dwell in it for before escaping to the stable steady state, thus creating rhythmic transients.
Revised:  This area allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients.
Edit intent: clarity
Original:  Zhigalov, Kaplan,  Palva (Clin Neurophysiol 2016;127:2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Revised:  Zhigalov, Kaplan, and Palva (Clin Neurophysiol 2016;127:2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Edit intent: clarity
Original:  However, the causal relations between these neuronal Long Range Temporal Correlations, sustained attention, and any avalanche dynamics are called into question, as is the assertion of Zhigalov et al.  that the neurofeedback flashes are unconsciously processed rather than capturing attention.
Revised:  However, the causal relations between these neuronal Long Range Temporal Correlations, sustained attention, and any avalanche dynamics are called into question, as is Zhigalov et al. that the neurofeedback flashes are unconsciously processed rather than capturing attention.
Edit intent: clarity
Original:  However, the causal relations between these neuronal Long Range Temporal Correlations, sustained attention, and any avalanche dynamics are called into question, as is the assertion of Zhigalov et al.  that the neurofeedback flashes are unconsciously processed rather than capturing attention.
Revised:  However, the causal relations between these neuronal Long Range Temporal Correlations, sustained attention, and any avalanche dynamics are called into question, as is the assertion of Zhigalov et al. 's assertion that the neurofeedback flashes are unconsciously processed rather than capturing attention.
Edit intent: fluency
Original:  Uncorrected concerns about false discovery rate and an objective mathematical error in the cited foundational work for the study of Zhigalov et al.  are also raised.
Revised:  Uncorrected concerns about false discovery rate and an objective mathematical error in the cited foundational work for Zhigalov et al. are also raised.
Edit intent: clarity
Original:  Uncorrected concerns about false discovery rate and an objective mathematical error in the cited foundational work for the study of Zhigalov et al.  are also raised.
Revised:  Uncorrected concerns about false discovery rate and an objective mathematical error in the cited foundational work for the study of Zhigalov et al. 's study are also raised.
Edit intent: clarity
Original:  Accordingly, micro-behaviours produced by  separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation in the model have macroscale consequences causally influencing the power-scaling of long-range temporal correlations.
Revised:  Accordingly, micro-behaviours produced by the model's separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation in the model have macroscale consequences causally influencing the power-scaling of long-range temporal correlations.
Edit intent: fluency
Original:  Accordingly, micro-behaviours produced by  separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation in the model have macroscale consequences causally influencing the power-scaling of long-range temporal correlations.
Revised:  Accordingly, micro-behaviours produced by separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation have macroscale consequences causally influencing the power-scaling of long-range temporal correlations.
Edit intent: clarity
Original: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Revised: Critical branching is a theoretical interaction in-between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Edit intent: clarity
Original: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Revised: Critical branching is a form of theoretical interaction between simple units, such as neuronal elements of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Edit intent: clarity
Original: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Revised: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Edit intent: clarity
Original: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( Clin Neurophysiol 2016 ;
Revised: Critical branching is a form of theoretical interaction between simple units, which, in the case of the human brain are assumed to be neuronal elements . Zhigalov, Kaplan, and Palva ( 2016 ;
Edit intent: coherence
Original:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Revised:  127 :2882-89) revealed that neurofeedback flash stimulation locked to the phase of high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Edit intent: clarity
Original:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Revised:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Edit intent: clarity
Original:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Revised:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital averages in the alpha-band. This feedback also influences the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Edit intent: clarity
Original:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations of alpha-band amplitude fluctuations.
Revised:  127 :2882-89) revealed that neurofeedback flash stimulation phase-locked to high-amplitude occipital alpha influences the stimulus-locked occipital alpha-band averages and the power scaling of long-range temporal correlations in alpha-band amplitude fluctuations.
Edit intent: clarity
Original:  At first, it might seem that neurofeedback influenced critical branching alongside there being an interaction between ongoing neuronal activity and evoked responses.
Revised:  Seemingly, neurofeedback influences critical branching alongside there being an interaction between ongoing neuronal activity and evoked responses.
Edit intent: coherence
Original:  However, the causal relations between these neuronal Long Range Temporal Correlations , sustained attention, and any avalanche dynamics are called into question , as is Zhigalov et al.
Revised:  However, the causal relations between these neuronal long-range temporal correlations , sustained attention, and any avalanche dynamics are called into question , as is Zhigalov et al.
Edit intent: fluency
Original:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to  single-trial flash-evoked event-related potentials  separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Revised:  Without critical branching, an alternative set of illustrative mathematical principles offers a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to single-trial flash-evoked event-related potentials separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Edit intent: fluency
Original:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to  single-trial flash-evoked event-related potentials  separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Revised:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data . That is, neurofeedback influences the deterministic contribution to single-trial flash-evoked event-related potentials separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Edit intent: coherence
Original:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to  single-trial flash-evoked event-related potentials  separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Revised:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to the single-trial flash-evoked event-related potentials separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Edit intent: fluency
Original:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to  single-trial flash-evoked event-related potentials  separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Revised:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to single-trial event-related potentials separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Edit intent: fluency
Original:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to  single-trial flash-evoked event-related potentials  separately from the neurofeedback flash-evoked gain in the amplitude of those oscillations .
Revised:  Without critical branching, an alternative set of illustrative mathematical principles offered a preliminary fit to the effects in the data , whereby neurofeedback influenced the deterministic contribution to single-trial flash-evoked event-related potentials separately from the oscillatory alpha gain that those flashes cause .
Edit intent: clarity
Original:  Accordingly, micro-behaviours produced by the model's separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation have macroscale consequencescausally influencing the power-scaling of long-range temporal correlations  .
Revised:  Accordingly, distinct principles of this neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation have macroscale consequencescausally influencing the power-scaling of long-range temporal correlations .
Edit intent: clarity
Original:  Accordingly, micro-behaviours produced by the model's separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation have macroscale consequencescausally influencing the power-scaling of long-range temporal correlations  .
Revised:  Accordingly, micro-behaviours produced by the model's separate principles of neurofeedback-related exponential occipital oscillatory alpha gain and deterministic event-related potential generation produce micro-behaviours with macroscale consequences: neurofeedback causally influences power-scaling of long-range temporal correlations .
Edit intent: clarity
Original: We study the empirical properties of realized volatility of the E-mini S P 500 futures contract at various time scales, ranging from a few minutes to one day.
Revised: We P 500 futures contract at various time scales, ranging from a few minutes to one day.
Edit intent: clarity
Original:  We propose a new method that is based on a decomposition of the distribution to be estimated in terms of so-called distribution elements (DEs).
Revised:  We propose a new method that is based on a decomposition of the unknown distribution in terms of so-called distribution elements (DEs).
Edit intent: clarity
Original:  These elements enable an adaptive and hierarchical discretization of the sample space with small or large elements in regions with high and variable or low densities, respectively.
Revised:  These elements enable an adaptive and hierarchical discretization of the sample space with small or large elements in regions with smoothly or highly variable densities, respectively.
Edit intent: clarity
Original:  The  refinement strategy that we propose is based on statistical goodness-of-fit and  independence tests that evaluate the local approximation of the distribution in terms of DEs.
Revised:  The novel refinement strategy that we propose is based on statistical goodness-of-fit and independence tests that evaluate the local approximation of the distribution in terms of DEs.
Edit intent: clarity
Original:  The non-applicability and numerical refutations of existing extended formulations results (such as Braun et al. (2015) ** or Fiorini et al. (2015) *** in particular) are briefly discussed in an appendix. 
Revised:  The non-applicability and numerical refutations of existing extended formulations results (such as Braun et al. (2015) or Fiorini et al. (2015) *** in particular) are briefly discussed in an appendix. 
Edit intent: fluency
Original:  The non-applicability and numerical refutations of existing extended formulations results (such as Braun et al. (2015) ** or Fiorini et al. (2015) *** in particular) are briefly discussed in an appendix. 
Revised:  The non-applicability and numerical refutations of existing extended formulations results (such as Braun et al. (2015) ** or Fiorini et al. (2015) in particular) are briefly discussed in an appendix. 
Edit intent: fluency
Original: We present a polynomial-sized linear program (LP) for the n-city TSP drawing upon "complex flow" modeling ideas by the first two authors who used an O(n ^9) xO(n^8) model*.
Revised: We present an O(n ^9) xO(n^8) model*.
Edit intent: clarity
Original:  We do not model explicit cycles of the cities, and our modeling does not involve the city-to-city variables-based, traditional TSP polytope referred to in the literature as " The TSP Polytope ." Optimal TSP objective value and tours are achieved by solving our proposed LP.
Revised:  We do not model explicit cycles of the cities, and our modeling does not involve the city-to-city variables-based, traditional TSP polytope referred to in the literature as " the TSP polytope ." Optimal TSP objective value and tours are achieved by solving our proposed LP.
Edit intent: fluency