essays on mind

Attempting a toy model of vertebrate understanding

Tag: phototaxis

Essay 25: head direction gradients

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On December 14, 2023

In Uncategorized

Essay 24, which investigated temporal gradient navigation, raised the question of head direction and navigation. The essay 24 model followed a zebrafish phototaxis experiment by [Chen and Engert 2014] which created a virtual light spot surrounded by darkness. The phototaxis behavior used Hb.m (medial habenula) and B.ip (interpeduncular nucleus) path using 5HT (serotonin) from V.mr (median raphe) as an average integrator [Cheng et al 2016] to generate the gradient without using head direction. Since B.ip receives head direction input [Petrucco et al 2023], essay 25 explores using head direction with the phototaxis gradient.

In the fruit fly drosophila, head direction and goal direction combine in the fan-shaped body to produce motor commands toward the goal [Matheson et al 2022]. Since the vertebrate B.ip connectivity with head direction resembles the fan-shaped body, this essay will use it as a model.

B.ip connectivity

Head direction from B.dtg (dorsal tegmental nucleus of Gudden) and the photo-gradient input from Hb.m would combine in tabular rows and columns in B.ip, if it resembles the fan-shaped body.

B.ip connectivity following a fan-shaped body model. B.dtg dorsal tegmental nucleus of Gudden, B.ip interpeduncular nucleus, B.rs reticulospinal motor command, Hb.m medial habenula.

Head direction encoding

Head direction is necessarily encoded by neurons. Each neuron in the head direction population has a specific direction, and fires when the animal is heading toward the neuron’s preferred direction.

Head direction encoding. Each neuron (colored box) corresponds to a direction. The neuron in the current direction is active, while other directions are silent.

In general, the heading is encoded is an ensemble of neurons, where several neurons around the actual direction fire at different rates (or possibly delayed phases). In the diagram above, the central direction (blue) has a higher activity while neighboring neurons have smaller values [Petrucco et al 2023].

Drosophila uses a coding for its head direction, where the amplitude of the actual direction neuron is close to one and the neurons at orthogonal directions are zero [Westeinde et al 2022]. This sinusoidal encoding enables neuron-friendly transformations and combinations [Touretzky et al 1993] with advantages over neural rate-encoding or phase encoding, particularly in response speed.

Fan-shaped body: allocentric to egocentric

Fruit fly navigation uses its fly-shaped body to combine an allocentric goal direction with the head direction to create motor commands to turn left or right. Egocentric is self-focused and allocentric is other-focused. Allocentric coordinates are animal-independent like North or toward a distant landmark, which egocentric coordinates are relative to the animal, like forward, right or left.

The fan-shaped body has a tabular shape where each column is a head direction and each row is a goal input [Hulse et al 2021]. The fan-shaped body combines the goal vector and the head direction to create motor commands [Westeinde et al 2022].

The fan-shaped body combines head direction with goal vectors to produce motor commands.

By shifting the head direction and combining the sinusoidal encodings of the goal vector, the motor output is a turn toward left or right. In drosophila, there’s a third motor command for a U-turn when the goal is behind the fly. Each motor command is carried by a specific neuron: PFL2.L (left), PFL2.R (right), and PFL3 (U-turn).

In drosophila, there are 18 distinct head direction columns and up to 9 goal rows. The fan-shaped body is also used for motivation calculations like sleep, despite sleep not fitting into the strict tabular model shown above. To create the strict organization, the fan-shaped body has 400 distinct neuron types [Hulse et al 2021].

Constructing goal vectors

In the phototaxis situation as in essay 24 or [Chen and Engert 2014] the goal vector is constructed from the gradient as the animal enters darkness from light and the head direction at that moment.

Captured goal vector (red) when the animal crosses into darkness.

As the diagram above suggests, the stored vector isn’t the true direction from light to dark, but only the sample along the animal’s path. The gradient value is then stored in the goal direction cells.

Storing the goal vector requires gating based on head direction. In zebrafish, serotonin accumulators can be gated by actions and used as a short term memory (5s – 20s) [Kawashima et al 2016]. For the essay, head dir gates serotonin accumulation as a replacement for the action gating.

Storing gradient into the goal vector based on the current goal. The red direction (south-east) gates its associated serotonin accumulator.

Since V.mr (median raphe) neurons produce consistent tonic oscillations, they are ideal for reading the accumulated value. No additional circuitry for the read is necessary.

Essay simulation

Because the essay model is a functional level, not a circuit level, it can use a directional vector encoding: a pair of floating-point numbers for direction and gradient for strength.

The simulation also calculated two averages: a short-term average for the goal vector gradient and a long-term average for phototaxis gradient motivation. The goal vector average needs to be shorter to avoid bleed-over from a previous direction.

Screenshot of animal crossing into darkness.

The above screenshot shows the animal’s state when it crosses into darkness. The long-timescale motivational gradient (“gr/grad”) is negative, driving the animal to avoid darkness. The short directional gradient (“sa”) is near zero, avoiding update of the stored goal vector. (Note: gradients are 0.5-centered for graphing consistency.)

The homunculus diamond in the upper right shows the current head direction (black semicircle pointing north-east) and the avoidance goal vector (orange semi-circle pointing east). Since the animal is heading toward the avoidance direction, it has a U-turn motor command (orange triangle at top). In addition, since the goal vector and head direction are near a right angle, right turns are inhibited (red at lower right). Because locomotion remains exploratory and stochastic, inhibits reduce turn probability but don’t force turns.

Discussion

This essay’s model is more speculative even compared to other essays, because I haven’t found any papers reporting in B.ip head direction behavior other than the base existence of head direction afferents [Petrucco et al 2023]. In particular, the drosophila fan-shaped body is not homologous to B.ip because the pre-vertebrate animal amphioxus lacks either structure. Nevertheless, it’s interesting that a goal gradient vector circuit is at least possible and relatively simple.

Specifically, the goal vector provides an evolutionary step toward hippocampal (E.hc) object vector cells and grid cells, because those are relatively small enhancements over the goal vector. Without a Bi.ip goal vector system as an intermediary step, hippocampal navigation is too big of an evolutionary step with too many concurrent requirements to be likely.

Note that the hippocampal system is strongly connected with the Hb, B.ip, V.mr, B.dtg system from this essay. E.hc (hippocampus), P.ms (medial septum), Hb (habenula), B.ip (interpeuncular nucleus), V.mr (median raphe), B.dtg (head direction) form a strong connected system together with H.sum (supramammilary/ retromammilary nucleus).

References

Chen X, Engert F. Navigational strategies underlying phototaxis in larval zebrafish. Front Syst Neurosci. 2014 Mar 25;8:39.

Cheng RK, Krishnan S, Jesuthasan S. Activation and inhibition of tph2 serotonergic neurons operate in tandem to influence larval zebrafish preference for light over darkness. Sci Rep. 2016 Feb 12;6:20788.

Hulse, B. K., Haberkern, H., Franconville, R., Turner-Evans, D., Takemura, S. Y., Wolff, T., … & Jayaraman, V. (2021). A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection. Elife, 10.

Kawashima T, Zwart MF, Yang CT, Mensh BD, Ahrens MB. The Serotonergic System Tracks the Outcomes of Actions to Mediate Short-Term Motor Learning. Cell. 2016 Nov 3;167(4):933-946.e20. 

Matheson, A. M., Lanz, A. J., Medina, A. M., Licata, A. M., Currier, T. A., Syed, M. H., & Nagel, K. I. (2022). A neural circuit for wind-guided olfactory navigation. Nature Communications, 13(1), 4613.

Petrucco L, Lavian H, Wu YK, Svara F, Štih V, Portugues R. Neural dynamics and architecture of the heading direction circuit in zebrafish. Nat Neurosci. 2023 May;26(5):765-773. 

Touretzky, D. S., Redish, A. D., & Wan, H. S. (1993). Neural representation of space using sinusoidal arrays. Neural Computation, 5(6), 869-884.

Westeinde Elena A., Emily Kellogg, Paul M. Dawson, Jenny Lu, Lydia Hamburg, Benjamin Midler, Shaul Druckmann, Rachel I. Wilson (2022). Transforming a head direction signal into a goal-oriented steering command. bioRxiv 2022.11.10.516039; 

Essay 24: phototaxis problems

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On December 7, 2023

In Uncategorized

The simple phototaxis implementation exposes a few problem with the simulation, both from running it and from reviewing neuroscience to critique it.

Interrupts

The essay doesn’t currently implement any interrupt mechanism. When running into darkness, the animal turns around and starts an area restricted search (ARS), but if the animal is in the middle of a long Levy path, it will cross the border and the search will not find the border.

Long initial paths breaks the phototaxis algorithm.

The problem here is that the ARS starts too late because the animal doesn’t interrupt the current behavior when encountering the border.

One solution is to create an interrupt (orientation) system, which exists in the vertebrate brain in V.ppt (peduncular pontine nucleus), and uses ACh (acetylcholine) to interrupt the current behavior. A natural location for the interrupt is V.ppt for the signal and the stratum as the plan representation, interruptible via ACh interrupts to the striatum.

Another solution is to avoid the uninterruptible behavior entirely, where the problem is the essay’s Levy walk implementation. The essay pre-computes the length of a run instead of continuously creating extensions. In contrast the zebrafish larva swims in bouts, but longer runs are made of multiple forward bouts.

Zebrafish random walk (ARTR area)

The essay’s random walk does not match actual zebrafish search behavior. The essay uses a turn-and-run model where the turn and run length are computed randomly. The zebrafish has a hindbrain oscillator, the ARTR (anterior rhombencephalic turning region) which selects left and right turns [Karpenko et al 2020].

Speculative directed random walk with the zebrafish ARTR. The isthmus is the midbrain-hindbrain boundary (MHB). B.artr anterior rhombencephalic turning region, B.rs reticulospinal motor command, Hb.m medial habenula, M.ip interpeduncular nucleus.

In zebrafish, turns and runs are selected independently and can be chained differently. Instead of turn-run-turn-run as in the essay, the zebrafish can have turn-turn or run-run patters. Zebrafish turn direction is also correlated, as opposed to the random walk’s turn independence. A zebrafish left turn is more likely to follow a left turn.

When encountering darkness, the same-direction turns increase. When encountering light, alternating turns increase. Together with the sharp turn (O-bend) followed b shallower turns, this behavior should create a spiral-like search for the light area.

Note: this specialized circuitry in the hindbrain suggests that random search is a primitive behavior. Although the essay put the Levy walk logic in the midbrain, it belongs in the more primitive hindbrain.

Head direction

[Petrucco et al 2023] report that M.ip is highly connected with head direction axons from B.dtg (dorsal tegmental area of Gudden). This head direction does not receive vestibular input, but is likely derived from motor efferent copies. Since both M.ip and B.dtg are r1-derived regions and possibly ante-vestibular, this head-direction and M.ip connection may be ancient.

Speculative M.ip circuit following the fruit fly fan-shaped body. B.dtg dorsal tegmental nucleus of Gudde, B.rs reticulospinal motor command, Hb.m medial habenula, M.ip interpeduncular nucleus.

This organization is strikingly similar to the fruit fly’s ellipsoid body (EB), protocerebral bridge (PB), and fan-shaped body (FB) in the central complex (CX) [Hulse et al 2021]. EB and PB calculate head direction. The fan-shaped body merges head direction with goal direction to produce motor commands. In this diagram, M.ip represented as if it resembles the fan-shaped body.

If the M.ip functionality is similar to the fan-shaped body, it’s highly likely to be convergent evolution, not homology because amphioxus lacks any similar structure.

Dark search

When zebrafish are plunged into darkness, they initiate a search that continues for about five minutes. The darkness behavior increases speed and straight behavior [Horstick et al 2017]. In other words, phototaxis is not just gradient behavior but also has steady-state darkness behavior. Because zebrafish require light to hunt, darkness in itself is is an area to avoid.

The essay is purely gradient based and has no speed changes. Photokinesis is moving faster in darkness and slower in light, which will bias the time spent in the light area.

References

Hulse, B. K., Haberkern, H., Franconville, R., Turner-Evans, D., Takemura, S. Y., Wolff, T., … & Jayaraman, V. (2021). A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection. Elife, 10.

Horstick EJ, Mueller T, Burgess HA. Motivated state control in larval zebrafish: behavioral paradigms and anatomical substrates. J Neurogenet. 2016 Jun;30(2):122-32.

Karpenko S, Wolf S, Lafaye J, Le Goc G, Panier T, Bormuth V, Candelier R, Debrégeas G. From behavior to circuit modeling of light-seeking navigation in zebrafish larvae. Elife. 2020 Jan 2;9:e52882. 

Petrucco L, Lavian H, Wu YK, Svara F, Štih V, Portugues R. Neural dynamics and architecture of the heading direction circuit in zebrafish. Nat Neurosci. 2023 May;26(5):765-773. doi: 10.1038/s41593-023-01308-5. 

Essay 24: Phototaxis – apical locomotion

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On December 5, 2023

In Uncategorized

Although the previous essays have focused on bilateral locomotion in the style of Braitenberg machines, the chimaera brain hypothesis [Tosches and Adrendt 2013] suggests a distinct apical form of locomotion. The chimaera brain hypothesis suggests that bilaterian brains are the merger of an apical nervous system from the ancestral zooplankton larva state and a blastoporal (bilateral) nervous system from paired muscles along the spinal cord. The apical area contains unpaired light and chemical sensors and the blastoporal area contains bilateral, topographic somatic sense like touch. Apical navigation require a temporal gradient, calculated by sequential sampling because the apical senses are non-directional.

Apical unpaired light sensors and bilateral paired touch sensors in the chimaera brain.

The essays’ simulation scenario is a temporal phototaxis based on the real-time place preference (RTPP) experiments of [Chen et al 2014], where a zebrafish stayed inside a virtual light circle, avoiding surrounding dark area. Temporal phototaxis is gradient-based locomotion, heading toward light and away from darkness by comparing light samples at different times.

Chimaera locomotor

The vertebrate paired eye and paired olfaction are late vertebrate developments. The pre-vertebrate animal amphioxus has only a single frontal eye. Since pre-paired sense animals needed to navigate toward opportunities and away from threats, it’s conceivable that apical random-walk navigation developed before visual navigation.

Dual navigation system based on both temporal gradient-based random walks and bilateral spatial gradient navigation.

Apical gradient

The apical area contains undirected light and chemical sensors. The apical area is based on the zooplankton larval state as shown below, while the bilateral area is based on bilateral worm-like adults structured like the spinal cord of paired muscles and neurons.

Apical zooplankton with cilia navigation.
Apical zooplankton larva. Note the single sensor on top.

Apical navigation requires following a temporal gradient, calculated by sequential sampling. While bilateral areas can compare left and right senses to calculate a spatial gradient, the single apical sense is restricted to a temporal gradient.

Bacteria tumble and run

Even simple bacteria can follow gradients using a directed random walk strategy called tumble and run [Segall et al 1986]. The bacteria’s flagella have two modes: tumble, turning without moving, and run, moving forward without turning. By alternating tumble with run, the bacteria can search with a random walk. By extending the run phase when the gradient improves, the bacteria can move toward the target.

Importantly, a temporal gradient calculation needs some sort of memory, accumulator or integrator to compare the current value to recent values. In bacteria, tis accumulator is an internal chemical quantity.

Different turning behavior depending on the gradient. Sharp turns moving into darkness and straight movement into light.

Apical and bilateral sensors

Amphioxus is a pre-vertebrate chordate that’s studied to understand vertebrate evolution. Amphioxus does not have a paired eye, instead it has a single frontal eye that amphioxus uses to orient vertically, and also a pineal-like photoreceptor [Lacalli 2020].

Chimera sense. Paired bilateral touch and unpaired apical photosensors.

The pineal region is near the vertebrate habenula. Amphioxus does not have a habenula, but it does have a nearby motor control neuron, LPN3, with similar genetic markers [Bozzo et al 2023]. Modern vertebrate medial habenula receives undirected light input from the retina, but it seems plausible that an early habenula used the pineal photosensor because both are part of the same epithalamus complex, and only later connected to the newly-paired retina when it developed.

Multiple apical regions

Before diving into the vertebrate areas for apical locomotion, I need to explain why widespread areas can all be apical, including midbrain and hindbrain areas. Vertebrates had two rounds of whole genome duplication [Dehal and Moore 2005], which gives an easy evolutionary opportunity for four apical areas from the genome duplication, in addition to other possible duplications. The xenobot experiments [Blackiston et al 2023] shows that biology can mix multiple copies like the split apical area into a coherent animal: development can be flexible.

Functional vertebrate brain model showing apical areas as marked by fgf8 development transcription factor.

The diagram above is a functional representation of the vertebrate brain with possible apical areas highlighted in blue. Fgf8 is a development growth factor associated with the apical area [Marlow et al 2014]. The four (or five) possible apical area are as follows:

  • Prefrontal cortex and olfactory bulb.
  • The caudal isthmus area (r1) at the midbrain-hindbrain boundary, including cerebellum (CB), interpeduncular nucleus (M.ip), midbrain locomotor (MLR, M.ppt, M.ldt), head direction (B.dtg), parabrachial (B.pb), and part of the substantia nigra (Snr).
  • Habenula (Hb) and pre-thalamic eminence area (P.em) near ZLI. Also, between the septum-diagonal band (P.msdb) and preoptic area (Poa) near the optic (retina) region (R).
  • The mammilary and supramammilary area of the hypothalamus (H.mb and H.sum).

I’ve listed four regions instead of the five blue areas because the Hb-P.em-P.msdb area are physical closer than the diagram suggests, are split more by the alar/basal division than distance, and is complicated by distortions from the paired optic region.

This essay uses functions from the r1 isthmus area (M.ip and MLR.α / M.ldt), and from the habenula / retinal area (Hb.m, P.em, pineal, and retina). The logic behind their connectivity is a function split-and-pull like taffy or continental drift from a single pre-duplication area, for example, the isthmus apical area duplicating from an original pre-hypothalamus / retinal apical area.

As a note, the supramammilary area (H.sum) is highly connected with the area in this essay, but I’m postponing exploring its functionality for now.

Vertebrate apical and bilateral locomotor

Previously the essays used the bilateral locomotor path, going through the Vta (posterior tuberculum), tectum (OT), and midbrain locomotive region (MLR). The apical path runs through the medial habenula (Hb.m) and the interpeduncular nucleus (M.ip) before reaching the motor neurons.

Bilateral and apical locomotive paths. B.ll lateral line, B.rs reticulospinal motor neurons, B.ss somatosensory, Hb.m medial habenula, M.ip interpeduncular nucleus, MLR midbrain locomotive region, OT optic tectum, V.mr median raphe, 5HT serotonin.

The lamprey’s Hb.m supports locomotion for light, odor, and the lateral line [Stephenson-Jones et al 2012]. The lateral line is an aquatic sense for water flow, which allows fish to sense nearby objects. Although the exact functional division of phototaxis isn’t known, Hb.m, M.ip and the serotonin raphe nuclei (V.mr – 5HT) are all required [Cheng et al 2016].

For the essay’s simulation, I’m asking the integration and running average to the V.mr and 5HT, but this is something of a guess, because phototaxis integration hasn’t been measured. In the essay’s model, M.ip translates the light data and 5HT average into a gradient and into action.

Phototaxis actions

When zebrafish enter darkness from light, they immediately produce a large turn (O-bend) and start an area restricted search (ARS) [Fernandes et al 2012]. Later turns are smaller [Chen and Engert 2014].

For the essay, phototaxis gradient modifies the standard random walk. When entering darkness, M.ip increases the turn angle. When entering light, M.ip increases forward movement, extending the run.

Essay simulation showing the animal returning to light from darkness. The graph shows the gradient change when crossing the darkness boundary.

The above screenshot shows the animal crossing into darkness and returning to light. In the graph, “light” is the current photosensor value, “avg” is the running average measured by serotonin neurons, and “grad” is the different between the two. A gradient drop triggers high angle turns. A gradient rise triggers straight movement.

As the heat map in the right shows, this simple system produces real-time place avoidance (RTPA) of darkness. Since the system has no learning, there’s no conditioned place aversion (CPA).

Prethalamic eminence

The full phototaxis circuit in vertebrates is a bit more complicated because light input does through an intermediate area called the pre-thalamic eminence (P.em), which is between the habenula, hypothalamus and thalamus, and it one of the apical areas. Although P.em is not cortical, it provides neurons necessary for cortical development (Cajal-Retzius neurons for L1 patterning) [Marin-Padilla 2015] and neurons for habenula input, the habenula-projecting pallidum (P.hb) [Stephenson-Jones 2016].

Apical navigation paths, simplified in lamprey and extended in mammals. E.hc hippocampus, Hb.m medial habenula, M.ip interpeduncular nucleus, MLR midbrain locomotive region, Ob olfactory bulb, P.em pre-thalamic eminence, P.hb habenula projecting pallidum, R.gc retina ganglion cells.

Retina input goes through P.em to Hb.m for phototaxis. Interestingly, the main input for Hb.m in mammals is via cells that migrate from P.em and become the posterior septum (P.ps) [Watanabe et al 2018], which receives almost all of its input from the hippocampus (E.hc). If the hippocampus is an odor-processing system, then the olfactory bulb (Ob) to E.hc to Hb.m path is a chemotaxis path matching the retina’s phototaxis path.

Note that the olfactory placed develops from the lens placed and is differentiated by fgf8 [Bailey et al 2006]. So, it’s pleasing that the similar olfactory and hippocampal paths to Hb.m is a are chemotaxis and phototaxis paths split from a common ancestor.

Speculation

Although the lateral and medial habenula are chemically, connectional, and developmentally distinct, their broad similarity is interesting. If the medial habenula supports direct, concrete sensory navigation by gradient descent, perhaps the medial habenula supports more abstract value-based navigation for more abstract goals.

References

Alonso A, Trujillo CM, Puelles L. Quail-chick grafting experiments corroborate that Tbr1-positive eminential prethalamic neurons migrate along three streams into hypothalamus, subpallium and septocommissural areas. Brain Struct Funct. 2021 Apr;226(3):759-785.

Bailey AP, Bhattacharyya S, Bronner-Fraser M, Streit A. Lens specification is the ground state of all sensory placodes, from which FGF promotes olfactory identity. Dev Cell. 2006 Oct;11(4):505-17. 

Blackiston D, Kriegman S, Bongard J, Levin M. Biological Robots: Perspectives on an Emerging Interdisciplinary Field. Soft Robot. 2023 Aug;10(4):674-686. 

Bozzo M, Bellitto D, Amaroli A, Ferrando S, Schubert M, Candiani S. Retinoic Acid and POU Genes in Developing Amphioxus: A Focus on Neural Development. Cells. 2023 Feb 14;12(4):614.

Chen X, Engert F. Navigational strategies underlying phototaxis in larval zebrafish. Front Syst Neurosci. 2014 Mar 25;8:39.

Cheng RK, Krishnan S, Jesuthasan S. Activation and inhibition of tph2 serotonergic neurons operate in tandem to influence larval zebrafish preference for light over darkness. Sci Rep. 2016 Feb 12;6:20788. 

Dehal P, Boore JL. Two rounds of whole genome duplication in the ancestral vertebrate. PLoS Biol. 2005 Oct;3(10):e314. 

Fernandes A. M., Fero K., Arrenberg A. B., Bergeron S. A., Driever W., Burgess H. A. (2012). Deep brain photoreceptors control light-seeking behavior in zebrafish larvae. Curr. Biol. 22, 2042–2047

Lacalli Thurston 2022 An evolutionary perspective on chordate brain organization and function: insights from amphioxus, and the problem of sentience Phil. Trans. R. Soc.

Marín-Padilla M. Human cerebral cortex Cajal-Retzius neuron: development, structure and function. A Golgi study. Front Neuroanat. 2015 Feb 27;9:21.

Marlow, Heather, et al. “Larval body patterning and apical organs are conserved in animal evolution.” BMC biology 12.1 (2014): 1-17.

Segall J. E., Block S. M., Berg H. C. (1986). Temporal comparisons in bacterial chemotaxis. Proc. Natl. Acad. Sci. U.S.A. 83, 8987–8991

Stephenson-Jones M, Floros O, Robertson B, Grillner S. Evolutionary conservation of the habenular nuclei and their circuitry controlling the dopamine and 5-hydroxytryptophan (5-HT) systems. Proc Natl Acad Sci U S A. 2012 Jan 17;109(3):E164-73.

Stephenson-Jones M, Yu K, Ahrens S, Tucciarone JM, van Huijstee AN, Mejia LA, Penzo MA, Tai LH, Wilbrecht L, Li B. A basal ganglia circuit for evaluating action outcomes. Nature. 2016 Nov 10;539(7628):289-293. 

Tosches, Maria Antonietta, and Detlev Arendt. “The bilaterian forebrain: an evolutionary chimaera.” Current opinion in neurobiology 23.6 (2013): 1080-1089.

Watanabe K, Irie K, Hanashima C, Takebayashi H, Sato N. Diencephalic progenitors contribute to the posterior septum through rostral migration along the hippocampal axonal pathway. Sci Rep. 2018 Aug 6;8(1):11728. 

Wolf S, Dubreuil AM, Bertoni T, Böhm UL, Bormuth V, Candelier R, Karpenko S, Hildebrand DGC, Bianco IH, Monasson R, Debrégeas G. Sensorimotor computation underlying phototaxis in zebrafish. Nat Commun. 2017 Sep 21;8(1):651. 

Zhang BB, Yao YY, Zhang HF, Kawakami K, Du JL. Left Habenula mediates light-preference behavior in Zebrafish via an asymmetrical visual pathway. Neuron. 2017;93:914–28.

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