1. Locomotor and Hippocampal Processing Converge in the Lateral Septum
Hannah S. Wirtshafter, Matthew A. Wilson 
Current Biology 
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2. Figure 1
The LS Contains Cells whose Firing Rates Correlate with Positive and Negative Acceleration
(A) Brain section from implanted rat, showing the lateral septum and electrolytic lesions made after recording. The red arrows mark lesions at the tetrode tips.
(B) Schematic of the lateral septum. Red shaded area indicates area where about 95% of lesions were seen. Red Xs indicate the location of three other lesions.
(C) An example of a cell with a negative correlation to negative acceleration and a positive correlation to positive acceleration (an overall positive correlation with the magnitude of acceleration). The method of determining correlation is analogous to determining spatial firing fields and is as follows: acceleration per time (top left) and spike count were then determined as a function of acceleration (top right). Spike count per acceleration was than divided by time per acceleration (middle panel; see STAR Methods for more details). A cell was considered correlated to acceleration if the p value for a linear correlation to positive or negative acceleration was <0.05. In this example, the p value for the positive correlation is < (r2 = 0.87; F(1,17) = 118), and the p value for the negative correlation is < (r2 = 0.93; F(1,17) = 241). The lower panel shows an example period of acceleration and a corresponding raster plot.
(D) Same as (C) but an example of a cell with a positive correlation to negative acceleration and a negative correlation to positive acceleration (an overall negative correlation to the magnitude of acceleration). The p value for positive correlation < (r2 = 0.58; F(1,29) = 41.9); the p value for negative correlation < (r2 = 0.56; F(1,28) = 36.2).
(E) Same as (C) and (D) but an example of a cell with a significant linear correlation with negative acceleration (p < 0.001; r2 = 0.48; F(1,22) = 21.9) and no linear correlation with positive acceleration (p > 0.5; r2 = −0.04; F(1,22) = 0.05).
(F) Acceleration correlations for all LS cells in one session. Correlates are computed as in (C). Significant linear correlations are marked with a red best fit line; non-significant are marked in black. The same cells and recording session are depicted in Figure 2C. In some sessions, LFP magnitude was also correlated with the magnitude of acceleration; see Figure S2.
(G) Distribution of difference ratios between slopes for positive and negative acceleration. A slopes difference ratio was calculated for each cell, wherein a difference ratio of 0 means the absolute value of positive and negative slopes are the same and a value 1 means they are highly different. The difference ratio for the cell depicted in (B) is <0.01, the cell in (C) is 0.09, and the cell in (D) is 0.89.
(H) Mean r2 for all acceleration correlations. Error bars represent SE. Hatched bars signify relationships with negative acceleration; non-hatched bars are relationships with positive acceleration. Each color represents a group: blue is all cells; purple is significantly correlated cells; and green is non-correlated cells. The only significant within-group difference is between the mean r2 values of cells significantly correlated with negative and positive acceleration (two sample t test; t(273) = −2.5; p < ). All across-group comparisons are significant (two sample t test; all p < ).
(I) Distribution of r2 for all cells (top panels), compared with distributions for significantly correlated and non-correlated cells (bottom panels). Left panels are negative acceleration; right panels are positive acceleration. All distributions of significantly correlated cells are different than distributions of non-correlated cells (all KS test; p < ).
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3. Figure 2
The LS Contains Cells whose Firing Rates Correlate with Running Speed
(A) Example of an LS cell whose firing is positively correlated with speed. Correlations were found similarly to acceleration (see C and STAR Methods): the amount of time spent at each speed was calculated (top left) and used to normalize the spike count per speed (top right). Spike rate was then calculated and plotted against a (middle), and cell was considered correlated if p < In this example, r2 = 0.98, p < , F(1,19) = 836. The lower panel shows an example period of acceleration and a corresponding raster plot.
(B) Same as (A) but an example of an LS cell whose firing rate is negatively correlated with speed (r2 = 0.87; p < ; F(1,30) = 202).
(C) Speed correlations for all LS cells in one session. Correlations are computed as in (A). The same recording session and cells are represented as in Figure 1F. Significant linear correlations are marked with a red best fit line; non-significant are marked in black.
(D) Distribution of slopes for best fit lines for linear correlations with speed. A slope of 0 is marked with a dashed red line. About 64% of cells significantly correlated with speed have positive slopes, compared with 60% of cells overall, which is not significantly different (two sample t test; t(722) = 1.11; p > 0.05). This graph is truncated for viewing but contains over 95% percent of slopes.
(E) Mean r2 for all velocity correlations. All differences in means are significant (two-sample t test; p < ).
(F) Distribution of r2 for all cells (top panel) compared with distributions for significantly correlated and non-correlated cells (bottom panel).
(G) Diagram showing the populations of cells correlated with speed and acceleration. The majority of cells correlated with speed are also correlated with acceleration and vice versa. 29% of cells have correlations with neither speed nor acceleration.
See also Figure S3.
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4. Figure 3
Spiking Correlation with Speed and Acceleration Occurs in the Absence of Reward and Precedes and Follows Movement, Respectively
(A) The proportion of cells modulated by speed and acceleration during rewarded trials, exploration, and passive movement. There is a significantly different distribution of acceleration-correlated cells during rewarded trials as compared to passive movement (Pearson’s chi-squared test; X2(1, n = 494) = 7.87; p = 0.005).
(B) Out of acceleration-correlated cells, the proportion correlated with positive and negative acceleration during rewarded trials, exploration, and passive movement. All comparisons were not significant (Pearson’s chi-squared test; all p > 0.05).
(C) Example of spiking correlations with speed during exploration, calculated as in Figure 2A. Significant correlations are marked with a red best fit line.
(D) The same cells as in (C) during exploration but their correlations with acceleration, calculated as in Figure 1C. Significant correlations are marked with a red best fit line.
(E) Examples of spiking correlations with speed during passive movement, calculated as in Figure 2A. Significant correlations are marked with a red best fit line.
(F) The same cells as in (E) during passive movement but their correlations with acceleration, calculated as in Figure 1C. Significant correlations are marked with a red best fit line.
(G) Decoding (see Figures S4A and S4C) speed with shifted spike trains to determine whether spiking precedes or follows movement, with SE bars. Spike train shift is indicated in seconds on the x axis. Mean error in speed decoding measured only for speeds between 10 cm/s and 30 cm/s (see Figure S5A for decoding with all speeds). Mean error in speed decoding relative to error at 0 shift, marked with a dotted line. Shown is mean error over 10 sessions of maze running and decoding. Change below zero is improvement in decoding.
(H) Same as in (G), but error in acceleration decoding (see Figures S4B and S4D) measured only for accelerations with magnitudes between 20 cm/s2 and 100 cm/s2 (see Figure S5B for decoding with all accelerations). Shown is mean error over 9 sessions of maze running and decoding. Change below zero is improvement in decoding.
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5. Figure 4
During a Conditioning Task, LS Cells Change Firing during Cue and Reward
(A) Schematic showing the details of the conditioned approach task. An intertrial period of 30–90 s is followed by an 8 s conditioned stimulus (CS) period with light and sound cue. With the cues still on, a reward spout is inserted into the cage for 8 s. At the end of the reward period, the spout is withdrawn and the cue turned off.
(B) Examples of PSTHs of four LS cells that change firing during the cue and reward period of the conditioned approach task. Intertrial periods are marked in blue, the CS period is marked in green, and the reward period is marked in purple. All changes in firing rate during cue and reward are compared to the last 8 s in the intertrial period. (Upper left) The cell decreases firing during cue and increases firing during reward. (Upper right) Cell decreases firing during cue and slightly decreases firing during reward. (Lower left) Cell decreases firing during cue and reward. (Lower right) Cell increases firing during cue and does not change during reward. Other combinations of increase and/or decrease and/or stay the same were seen, but not pictured. See also Figure S6B.
(C) Cells that change firing during the conditioned approach task cannot be categorized as cells correlated to speed or acceleration (n = 223). Cells were considered to have changed firing at cue or reward if firing rate changed more than 20%. The populations of cue- and reward-modulated cells are not significantly different from one another in their makeup of speed- and acceleration-modulated cells (one-way ANOVA; f(5,18) = 0.17; p > 0.05).
(D) Cells that are correlated to speed or acceleration cannot be categorized as changing firing during cue or reward (n = 223). The populations of speed- and acceleration-modulated cells are not significantly different from one another in their makeup of cue- and reward-modulated cells (one-way ANOVA; f(3,8) = 0.46; p > 0.05).
(E) Diagram illustrating the overlap between cells that are correlated with speed or acceleration and cells correlated with cue and/or reward. 4% of cells were not modulated by speed, acceleration, cue, or reward.
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6. Figure 5
The Hippocampus Displays Similar Firing Patterns to the LS during Conditioning
(A) Examples of PSTHs of four examples of hippocampus cell responses on conditioned approach task. Intertrial periods are marked in blue, the CS period is marked in green, and the reward period is marked in purple. All changes in firing rate during cue and reward are compared to the last 8 s in the intertrial period. (Top left) Cell decreases firing during cue and increases firing during reward. (Top right) Cell decreases firing at cue and slightly decreases firing at reward. (Bottom left) Cell decreases firing at cue and reward. (Bottom right) Cell increases firing at cue and does not change firing at reward. Other combinations of increase and/or decrease and/or stay the same were also seen, but not pictured. See also Figure S6B.
(B) Quantification of cue and reward firing changes in the LS versus the hippocampus. LS firing is in blue; hippocampal firing is in purple. x axis shows the percent change in firing rate during cue (left) and reward (right), as compared to the previous 8 s in the intertrial interval. Distribution of firing rates is similar for LS and hippocampus cells during cue (KS test; p > 0.05) and reward (KS test; p > 0.05). Examples of LS and hippocampus cells at the minimum and maximum changes can be seen in Figure S6B.
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7. Figure 6 LS Cells Show Hippocampally Associated Spiking Activity
(A) PSTH of LS firing rate around ripple start time. Each line is the average firing of a cell around ripple start at 0 ms. Blue lines are cells that increased firing over 20% during a ripple; red lines are cells that did not. Bolded blue and purple lines are the averages for their respective populations.
(B) Distribution of circular concentration kappa for all LS cells, measuring degree of theta modulation. A cell was considered strongly modulated if it had a kappa >0.3, marked with a dotted line.
(C) Examples of three LS cells: not theta modulated; strongly theta modulated; and slightly theta modulated. (Top row) Spiking phase preference during theta measured from a CA1 tetrode is shown, normalized so theta phase 0 is maximum hippocampal spiking. (Bottom row) Autocorrelogram of the same cells is shown. See also Figure S7.
(D) Distribution of bits per spike for LS cells. Cutoff to be considered spatially modulated was 0.8, marked by a dotted line.
(E) Two examples of “place fields” in LS cells. (Left) An LS cell with place-selective firing at reward site is shown. Bits per spike = 0.8. (Right) LS cell with place-selective firing on center stem and forced choice point is shown. Bits per spike = 1.4.
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8. Figure 7
Speed- and Acceleration-Modulated Cells, as a Population, Have Unique Properties and Anatomical Connections Compared to Cue- and Reward-Modulated Cells
(A) Chart showing the cross tabulations of the likelihood of co-occurring modulations. Number is odds of finding the two modulations together (each ratio was calculated independently) as compared to the odds if the modulations were independent. Odds ratio and p values were calculated using Fisher’s exact test. p < 0.05 marked with one star; p < marked with two stars. Hippocampally correlated cells can be identified by the presence of ripple-modulated firing, theta-modulated firing, place-modulated firing, and response to cue and reward in the conditioned approach task. All three of these identifiers are co-occurring and occur separately from speed and acceleration modulation, which are highly covariant.
(B) We hypothesize that the movement information is coming from one of the many brainstem connections to the LS. The brainstem may send movement information from the septum, which is also receiving spatial and working memory information from the hippocampus. These convergences of these two inputs allow the LS to transmit spatial and contextual information, in concert with locomotor information, to downstream areas, such as the VTA, where value weighting occurs.
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