Chronux: A platform for analyzing neural signals

Bokil, Hemant; Andrews, Peter; Kulkarni, Jayant; Mehta, Samar B.; Mitra, Partha P.

doi:10.1016/j.jneumeth.2010.06.020

Cited by 786 publications

(658 citation statements)

References 25 publications

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“…In the hippocampus, prominent oscillations have been noted at (5-10 Hz), slow ␥ (30 -50 Hz), fast ␥ (50 -90 Hz), , and ripple (130 -230 Hz) frequencies (Belluscio et al, 2012). Although numerous studies point to the role of synaptic and nonsynaptic coupling of neurons in the generation of oscillations, specific mechanisms that support the various rhythms are not well understood (Buzsáki and Draguhn, 2004;Klausberger and Somogyi, 2008;Isaacson and Scanziani, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Neurons can communicate with each other either synaptically, electrically through gap junctions, or both (Tamás et al, 1998;Galarreta and Hestrin, 1999;Fukuda and Kosaka, 2000;Thomson et al, 2002). Electrical coupling has been observed chiefly among neurons of the same interneuron class (Galarreta and Hestrin, 1999;Tamás et al, 2000;Deans et al, 2001;Szabadics et al, 2001;Beierlein et al, 2003;Blatow et al, 2003;Galarreta et al, 2004;Mancilla et al, 2007;Fanselow et al, 2008) and has been postulated to promote fast spike synchronization (Traub et al, 2001;Gibson et al, 2005;Hughes and Crunelli, 2007;Mancilla et al, 2007). A recent in vitro study, however, suggested that millisecond synchrony between inhibitory interneurons can be equally well achieved by chemical synapses (Hu et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Millisecond Timescale Synchrony among Hippocampal Neurons

et al. 2014

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Inhibitory neurons in cortical circuits play critical roles in composing spike timing and oscillatory patterns in neuronal activity. These roles in turn require coherent activation of interneurons at different timescales. To investigate how the local circuitry provides for these activities, we applied resampled cross-correlation analyses to large-scale recordings of neuronal populations in the cornu ammonis 1 (CA1) and CA3 regions of the hippocampus of freely moving rats. Significant counts in the cross-correlation of cell pairs, relative to jittered surrogate spike-trains, allowed us to identify the effective couplings between neurons in CA1 and CA3 hippocampal regions on the timescale of milliseconds. In addition to putative excitatory and inhibitory monosynaptic connections, we uncovered prominent millisecond timescale synchrony between cell pairs, observed as peaks in the central 0 ms bin of cross-correlograms. This millisecond timescale synchrony appeared to be independent of network state, excitatory input, and ␥ oscillations. Moreover, it was frequently observed between cells of differing putative interneuronal type, arguing against gap junctions as the sole underlying source. Our observations corroborate recent in vitro findings suggesting that inhibition alone is sufficient to synchronize interneurons at such fast timescales. Moreover, we show that this synchronous spiking may cause stronger inhibition and rebound spiking in target neurons, pointing toward a potential function for millisecond synchrony of interneurons in shaping and affecting timing in pyramidal populations within and downstream from the circuit.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Millisecond Timescale Synchrony among Hippocampal Neurons

et al. 2014

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“…The frequency bands of low gamma, high gamma, and SWR were defined as 30-45, 60-90, and 150-250 Hz, respectively. For the first step of processing of LFP, we eliminated the direct current offset and slow fluctuations using MATLAB (MathWorks, Natick, MA), and the locdetrend function in Chronux 2.00 toolbox (Bokil et al 2010).…”

Section: Discussionmentioning

confidence: 99%

“…3SD for at least 15 ms. For the purpose of analyzing SWR associated with eating, we eliminated the data points for which the running speed was over 4 cm/s. We calculated SWR-triggered spectrograms using MATLAB (MathWorks, Natick, MA) and Chronux toolbox 2.00 (Bokil et al 2010). The window had a width of 100-ms and moved with 10-ms steps.…”

Section: Discussionmentioning

confidence: 99%

Within-session dynamics of theta–gamma coupling and high-frequency oscillations during spatial alternation in rat hippocampal area CA1

2014

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Theta-gamma coupling in the hippocampus is thought to be involved in cognitive processes. A large body of research establishes that the hippocampus plays a crucial role in the organization and maintenance of episodic memory, and that sharp-wave ripples (SWR) contribute to memory consolidation processes. Here, we investigated how the local field potentials in the hippocampal CA1 area adapted along with rats' behavioral changes within a session during a spatial alternation task that included a 1-s fixation and a 1.5-s delay. We observed that, as the session progressed, the duration from fixation onset to nose-poking in the choice hole reduced as well as the number of premature responses during the delay. Parallel with the behavioral transitions, the power of high gamma during the delay period increased whereas that of low gamma decreased later in the session. Furthermore, the strength of theta-gamma modulation later in the session showed significant increase as compared to earlier in the session. Examining SWR during the reward period, we found that the number of SWR events decreased as well as the power in a wide frequency range during SWR events. In addition, the correlation between SWR and gamma oscillations just before SWR events was higher in the earlier trials than in the later trials. Our findings support the notion that the inputs from CA3 and entorhinal cortex play a critical role in memory consolidation as well as in cognitive processes. We suggest that SWR and the inputs from the two areas serve to stabilize the task behavior and neural activities.

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“…Data were analysed using custom code written in MATLAB (Mathworks Inc.) and CHRONUX [19]. Both animals were trained on a standard memory-guided saccade task and the foraging search task (figure 1).…”

Section: (B) Electrophysiological Recordingmentioning

confidence: 99%

Evidence for differential top-down and bottom-up suppression in posterior parietal cortex

Mirpour

Bisley

2013

Phil. Trans. R. Soc. B

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When searching for an object, we usually avoid items that are visually different from the target and objects or places that have been searched already. Previous studies have shown that neural activity in the lateral intraparietal area (LIP) can be used to guide this behaviour; responses to task irrelevant stimuli or to stimuli that have been fixated previously in the trial are reduced compared with responses to potential targets. Here, we test the hypothesis that these reduced responses have a different genesis. Two animals were trained on a visual foraging task, in which they had to find a target among a number of physically identical potential targets (T) and task irrelevant distractors. We recorded neural activity and local field potentials (LFPs) in LIP while the animals performed the task. We found that LFP power was similar for potential targets and distractors but was greater in the alpha and low beta bands when a previously fixated T was in the response field. We interpret these data to suggest that the reduced single-unit response to distractors is a bottom-up feed-forward result of processing in earlier areas and the reduced response to previously fixated Ts is a result of active top-down suppression.

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Chronux: A platform for analyzing neural signals

Cited by 786 publications

References 25 publications

Millisecond Timescale Synchrony among Hippocampal Neurons

Millisecond Timescale Synchrony among Hippocampal Neurons

Within-session dynamics of theta–gamma coupling and high-frequency oscillations during spatial alternation in rat hippocampal area CA1

Evidence for differential top-down and bottom-up suppression in posterior parietal cortex

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