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Distribution, Amplitude, Incidence, Co-Occurrence, and Propagation of Human K-Complexes in Focal Transcortical Recordings(1,2,3).

Mak-McCully RA, Rosen BQ, Rolland M, Régis J, Bartolomei F, Rey M, Chauvel P, Cash SS, Halgren E - eNeuro (2015)

Bottom Line: KCs were marked manually on each channel, and local generation was confirmed with decreased gamma power.Locally generated KCs were found in all sampled areas, including cingulate, ventral temporal, and occipital cortices.These results open a novel view where KCs overall are universal cortical phenomena, but each KC may variably involve small or large cortical regions and spread in variable directions, allowing flexible and heterogeneous contributions to sleep homeostasis and memory consolidation.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Neurosciences, University of California, San Diego , San Diego, California 92093.

ABSTRACT
K-complexes (KCs) are thought to play a key role in sleep homeostasis and memory consolidation; however, their generation and propagation remain unclear. The commonly held view from scalp EEG findings is that KCs are primarily generated in medial frontal cortex and propagate parietally, whereas an electrocorticography (ECOG) study suggested dorsolateral prefrontal generators and an absence of KCs in many areas. In order to resolve these differing views, we used unambiguously focal bipolar depth electrode recordings in patients with intractable epilepsy to investigate spatiotemporal relationships of human KCs. KCs were marked manually on each channel, and local generation was confirmed with decreased gamma power. In most cases (76%), KCs occurred in a single location, and rarely (1%) in all locations. However, if automatically detected KC-like phenomena were included, only 15% occurred in a single location, and 27% occurred in all recorded locations. Locally generated KCs were found in all sampled areas, including cingulate, ventral temporal, and occipital cortices. Surprisingly, KCs were smallest and occurred least frequently in anterior prefrontal channels. When KCs occur on two channels, their peak order is consistent in only 13% of cases, usually from prefrontal to lateral temporal. Overall, the anterior-posterior separation of electrode pairs explained only 2% of the variance in their latencies. KCs in stages 2 and 3 had similar characteristics. These results open a novel view where KCs overall are universal cortical phenomena, but each KC may variably involve small or large cortical regions and spread in variable directions, allowing flexible and heterogeneous contributions to sleep homeostasis and memory consolidation.

No MeSH data available.


Related in: MedlinePlus

Template application to detect KC-like activity. Channel-specific templates were created for each subject by averaging from −350 to +650 ms on the most negative peak at time zero over the manually detected KCs in each channel (box at left). The channel-specific templates were then applied when a manually marked KC occurred in at least one channel. The templates were applied from −450 to +750 ms, with time zero representing the average time between the first and last manually chosen channel peaks within a KC. Four such examples from subject 6 are plotted vertically. Manually marked KCs are plotted in red. The maximum value of the sliding inner product between the signal and the template was taken over the blue highlighted window. If the value was above the 99th percentile of the  distribution for that channel and corresponded to the largest (or smallest) peak over the entire 1200 ms window, the KC was recorded as KC-like activity (KCs in blue), and if it was below the threshold, it was not (signal in black).
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Figure 8: Template application to detect KC-like activity. Channel-specific templates were created for each subject by averaging from −350 to +650 ms on the most negative peak at time zero over the manually detected KCs in each channel (box at left). The channel-specific templates were then applied when a manually marked KC occurred in at least one channel. The templates were applied from −450 to +750 ms, with time zero representing the average time between the first and last manually chosen channel peaks within a KC. Four such examples from subject 6 are plotted vertically. Manually marked KCs are plotted in red. The maximum value of the sliding inner product between the signal and the template was taken over the blue highlighted window. If the value was above the 99th percentile of the distribution for that channel and corresponded to the largest (or smallest) peak over the entire 1200 ms window, the KC was recorded as KC-like activity (KCs in blue), and if it was below the threshold, it was not (signal in black).

Mentions: The above analyses were performed on the manually marked KCs. The strict criteria used to select these phenomena, most notably that there was a flat baseline (i.e., no preceding oscillation) prior to the KC, may have prevented KC-like phenomena from being detected, and thus result in an underestimation of the degree of KC co-occurrence. In order to detect KC-like events, a template was created for each channel and applied at the times of manual KCs occurring in at least one channel (Fig. 8). A threshold was established as the 99th percentile of periods when no KC was visually present. Events that exceeded the template threshold were included as KC-like events (see Materials and Methods). Application of these individualized channel templates identified 13,383 KC-like events—a 96.8% increase in detected KCs—and 98.7% of the 13,821 manually marked KCs.


Distribution, Amplitude, Incidence, Co-Occurrence, and Propagation of Human K-Complexes in Focal Transcortical Recordings(1,2,3).

Mak-McCully RA, Rosen BQ, Rolland M, Régis J, Bartolomei F, Rey M, Chauvel P, Cash SS, Halgren E - eNeuro (2015)

Template application to detect KC-like activity. Channel-specific templates were created for each subject by averaging from −350 to +650 ms on the most negative peak at time zero over the manually detected KCs in each channel (box at left). The channel-specific templates were then applied when a manually marked KC occurred in at least one channel. The templates were applied from −450 to +750 ms, with time zero representing the average time between the first and last manually chosen channel peaks within a KC. Four such examples from subject 6 are plotted vertically. Manually marked KCs are plotted in red. The maximum value of the sliding inner product between the signal and the template was taken over the blue highlighted window. If the value was above the 99th percentile of the  distribution for that channel and corresponded to the largest (or smallest) peak over the entire 1200 ms window, the KC was recorded as KC-like activity (KCs in blue), and if it was below the threshold, it was not (signal in black).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4596022&req=5

Figure 8: Template application to detect KC-like activity. Channel-specific templates were created for each subject by averaging from −350 to +650 ms on the most negative peak at time zero over the manually detected KCs in each channel (box at left). The channel-specific templates were then applied when a manually marked KC occurred in at least one channel. The templates were applied from −450 to +750 ms, with time zero representing the average time between the first and last manually chosen channel peaks within a KC. Four such examples from subject 6 are plotted vertically. Manually marked KCs are plotted in red. The maximum value of the sliding inner product between the signal and the template was taken over the blue highlighted window. If the value was above the 99th percentile of the distribution for that channel and corresponded to the largest (or smallest) peak over the entire 1200 ms window, the KC was recorded as KC-like activity (KCs in blue), and if it was below the threshold, it was not (signal in black).
Mentions: The above analyses were performed on the manually marked KCs. The strict criteria used to select these phenomena, most notably that there was a flat baseline (i.e., no preceding oscillation) prior to the KC, may have prevented KC-like phenomena from being detected, and thus result in an underestimation of the degree of KC co-occurrence. In order to detect KC-like events, a template was created for each channel and applied at the times of manual KCs occurring in at least one channel (Fig. 8). A threshold was established as the 99th percentile of periods when no KC was visually present. Events that exceeded the template threshold were included as KC-like events (see Materials and Methods). Application of these individualized channel templates identified 13,383 KC-like events—a 96.8% increase in detected KCs—and 98.7% of the 13,821 manually marked KCs.

Bottom Line: KCs were marked manually on each channel, and local generation was confirmed with decreased gamma power.Locally generated KCs were found in all sampled areas, including cingulate, ventral temporal, and occipital cortices.These results open a novel view where KCs overall are universal cortical phenomena, but each KC may variably involve small or large cortical regions and spread in variable directions, allowing flexible and heterogeneous contributions to sleep homeostasis and memory consolidation.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Neurosciences, University of California, San Diego , San Diego, California 92093.

ABSTRACT
K-complexes (KCs) are thought to play a key role in sleep homeostasis and memory consolidation; however, their generation and propagation remain unclear. The commonly held view from scalp EEG findings is that KCs are primarily generated in medial frontal cortex and propagate parietally, whereas an electrocorticography (ECOG) study suggested dorsolateral prefrontal generators and an absence of KCs in many areas. In order to resolve these differing views, we used unambiguously focal bipolar depth electrode recordings in patients with intractable epilepsy to investigate spatiotemporal relationships of human KCs. KCs were marked manually on each channel, and local generation was confirmed with decreased gamma power. In most cases (76%), KCs occurred in a single location, and rarely (1%) in all locations. However, if automatically detected KC-like phenomena were included, only 15% occurred in a single location, and 27% occurred in all recorded locations. Locally generated KCs were found in all sampled areas, including cingulate, ventral temporal, and occipital cortices. Surprisingly, KCs were smallest and occurred least frequently in anterior prefrontal channels. When KCs occur on two channels, their peak order is consistent in only 13% of cases, usually from prefrontal to lateral temporal. Overall, the anterior-posterior separation of electrode pairs explained only 2% of the variance in their latencies. KCs in stages 2 and 3 had similar characteristics. These results open a novel view where KCs overall are universal cortical phenomena, but each KC may variably involve small or large cortical regions and spread in variable directions, allowing flexible and heterogeneous contributions to sleep homeostasis and memory consolidation.

No MeSH data available.


Related in: MedlinePlus