Tuesday, December 31, 2019

Cognitive and neuoscience related papers at NeurIPS


There seemed to be increasing numbers of cognitive and neuoscience related papers presented at NeurIPS (Neural Information Processing), a welcoming sign! Here are some from NeurIPS2019. Please let me know if you find some interesting ones missing.

















NeurIPS2020 will be in Vancouver, Canada.

Tuesday, December 13, 2016

Functional diagram of language areas

Despite numerous studies on functional mapping of language, characterization of language related areas is far from complete. Whether there is a map is a contentious issue in the first place. I don’t want to go into the philosophical debate, since I think it’s becoming clearer now that both sides (1) people who wants you to believe that brain is made of modules that can be labeled using terms defined in preexisting theories, and (2) people who think that that the cerebrum is just a homogeneous sheet of processing units are both wrong.

I do believe in the reality of linguistic units (phoneme, morpheme, phrases, etc.) and I am fond of learning various syntactic theories (government and binding, minimalism, HPSG, etc.), but I think it’s naive to assume that there are brain modules dedicated to levels of language representations and syntactic operations. I am very skeptical of Marr’s levels of design (computational / algorithmic / implementation) when it comes to the brain. Recent development in deep neural networks provides a good counter-example: we can design a processing system in which we cannot label the function of each component clearly, at least in terms of preexisting theories.

Having said that, I do not think that the cerebrum is just a homogeneous sheet. The most important structure obviously emerges from inputs and outputs as well as long and short range connecting fibers. Genes can modulate numerous parameters related to the formation of neo-cortex, although it does not look as heterogeneous as “old” organs (like the heart or subcortical areas) since there has not been nearly as much time historically to tweak these parameters.

So in short, I’ll start with inputs and outputs (for the nature of inputs and output see the appendix), and try to carefully characterize the working of local areas, paying full attention to the fact that traditional way of characterizing language areas may be totally wrong. Main source of information are the review papers by Friederici (2011), which summarizes numerous studies in the linguistic brain are summarized, and Hickok and Poeppel (2007), written by two of the powerhouse of knowledge and critical thinking in language.

Language related event related brain potentials (ERP) provide valuable insights, since ERP research has a rich history of critical works and also it provides timing information.

·      N100, associated with acoustic and phonological process, is localized around the auditory corterx.
·      ELAN (150mS), associated with syntactic category assignment, is localized  around anterior temporal / inferior frontal gyrus (IFG).
·      LAN (400mS), associated with morphosyntactic features for argument structures, is localized around anterior temporal gyrus/IFG.
·      N400, associated with lexical access load, is localized around mid-posterior superior temporal gyrus /IFG.
·      P600, associated with syntactic reanalysis (but can be semantically motivated), is localized around middle temporal gyrus/basal ganglia.

Results of MRI studies are harder to summarize. For one thing, stimulus conditions vary from one study to another. Also labels like “semantic”, “multimodal”, etc.  mean different things in different studies. For instance semantics as in thematic role assignment and word disambiguation are totally different.

So I focus focus on inputs, outputs, long-range connections, and the axes in the frontal and temporal areas along which the quality of information changes most dramatically.  The auditory input to the temporal lobe and the motor output to language related muscle control (see appendix) in the frontal lobe are clear. The output from the speech processing is less clear, seemingly go into higher area including the area 45. The input to the speech motor control is also unclear, which may consist of knowledge to be expressed and the motivation to speak. The main axis of qualitative variation, to me, appears to be the time-range. As the position in the language related cerebral cortex approaches the posterior end of the prefrontal cortex, or closer to the primary auditory cortex in the temporal lobe, the information seems to be more short term (e.g. a simple motor command or a short duration of certain speech spectrum). As the position approaches frontal end of the prefrontal cortex or furthest end from the primary auditory cortex, the information becomes long term (or even static), (e.g. an intended message content or a sentence or even a paragraph).

I will probably keep revising the diagram, but the figure below is the one I got for now.




Appendix: Subcortical language pathways

What kind of auditory signal does the primary auditory cortex (area 41) receive? The auditory pathway from the cochlea to the primary auditory cortex consists of Ventral and Dorsal Cochlear Nucleus, Superior Olivary Complex, Lateral Lemniscus, Inferior Colliculus, and Medial Geniculate Body. So by the time the signal reaches is area 41, it is already processed for directional information as well as for some speech related features such as complex spectrum and onset times. 

Speech motor control requires exquisite coordination of many muscles, so the output from the speech related primary motor cortex (inferior part of area 4, which in turn receives from area 6) goes out to many nerve tracts, including cranial (V:Trigmantal, VII: Facial, IX/X: Glosspharyngeal/Vagus, XII: Hypogrossal) and Laryngeal nerves. Besides these nerves from the primary motor cortex called pyramidal tracts, there are extrapyramidal speech tracts that goes from the cerebellum, premotor cortex via basal ganglia, and output to thalamus, which nevertheless do not directly innervate the lower motor neurons that control speech related muscles. Unlike the auditory signal pathway, coordination of these multiple output does not involve many lower level ganglions.




Caplan D. The neurobiological basis of language. Brain. 2007 May 1;130(5):1442-6.

Damasio AR, Geschwind N. The neural basis of language. Annual review of neuroscience. 1984 Mar;7(1):127-47.

Friederici AD. The brain basis of language processing: from structure to function. Physiological reviews. 2011 Oct 1;91(4):1357-92.

Hickok G, Poeppel D. The cortical organization of speech processing. Nature Reviews Neuroscience. 2007 May 1;8(5):393-402.

Stowe LA, Haverkort M, Zwarts F. Rethinking the neurological basis of language. Lingua. 2005 Jul 31;115(7):997-1042.


Tallal P, Miller S, Fitch RH. Neurobiological basis of speech: a case for the preeminence of temporal processing. Annals of the New York academy of sciences. 1993 Jun 1;682(1):27-47.

Monday, December 5, 2016

Structural connectivity among language areas

Leaving the cortical microstructure behind (at least temporarily), this week’s focus will be on the macro level, i.e. language related brain areas and interconnections among them. I’d like to start with the hardware (citoarchitectural area and structural connectivity level) and build up. Language related brain areas (this itself is a dubious labeling, since the areas mentioned may subserve non-linguistic functions – but I move on), focusing on the temporal and prefrontal cortices.

The temporal cortex here includes areas 41, 42, 21, and 20. The frontal cortex includes 45, 44, (prefrontal) and 6 (premotor). There are structural connections between anterior 22 (anterior) and 45 through Extreme Fiber Capsule System, and between anterior 22 and occluded part of the inferior frontal cortex (Frontal Operculum) through unicite fasciculus (Friederici 2011). Posteriorly there are structural connections between posterior 22 and 44, and between posterior 22 and 6 both served by Arcuate Fascile and Superior Longitudinal Facile III (Friederici 2011). Friederici 2011 focuses on peri-Sylvian cortex, but extending the scope a little to include so called lexical areas (21) and a sensory/motor hub (40) (Hickock and Poppel 2011), I get my Figure 1.

The auditory input flows from 41, 42, and from there flows both anteriorly through and posteriorly through area 22 and 21. The motor intention / control flow is from 45, 44, and to  6, where 6 connects to the motor output area. Fiber tracking in primate brain suggests that the ventral pathway runs from the temporal to prefrontal lobe, whereas the ventral pathway is considered bidirectional (Rauschcker 2011). From here I’d like to characterize processing taking place at each area, but it’s been long enough, so to be continued …



Friederici AD. The brain basis of language processing: from structure to function. Physiological reviews. 2011 Oct 1;91(4):1357-92.

Hickok G, Poeppel D. The cortical organization of speech processing. Nature Reviews Neuroscience. 2007 May 1;8(5):393-402.

Kelly C, Uddin LQ, Shehzad Z, Margulies DS, Castellanos FX, Milham MP, Petrides M. Broca’s region: linking human brain functional connectivity data and non‐human primate tracing anatomy studies. European Journal of Neuroscience. 2010 Aug 1;32(3):383-98.


Rauschecker JP. An expanded role for the dorsal auditory pathway in sensorimotor control and integration. Hearing research. 2011 Jan 31;271(1):16-25.

Thursday, November 17, 2016

More on Broca's area and cortical microcircuits

I just bought a nice book on Broca’s area called “Broca’s Region” (Eds. Grodzinsky and Amunts 2006). The book grew out of a workshop on Broca’s Region Workshop that took place in Juelich, Germany in 2004. I don’t know whether many people agree with Grodzinsky’s particular view of Broca’s area, but the book is nice regardless, especially since we can buy it used for several bucks now and it includes historical papers by Paul Broca and Norman Geschwind, to name a few. Unfortunately for me, its biological section focuses on mapping / localization of the Broca’s area and less on cortical microcircuits. It does show a multivariate analysis of cytoarchitectonic asymmetry, in that the Broca’s area (both BA44 and BA45) shows marked difference from BA6 (premotor and supplementary motor area) in the left hemisphere compared to the right hemisphere (Amunts and Zilles 2006).

Going back to Tardif’s 2007 paper, it mentions the asymmetry regarding the extent of horizontal connections in the Broca’s area. Bilaterally speaking (before going into asymmetry), supragranular tracer injection found horizontal extension of several mm found in in layers II, III, lesser in IV-VI.  Layer IV injection found horizontal extension up to 3.7 mm in I-IV, lesser in V, VI. Infragranular injection resulted in smaller extension confined within infragranular layers. In terms of asymmetry, more interlaminar difference in the horizontal extension was found in the left hemisphere.

Before concluding today’s blog, I’d like to take stock of what I know about generic (i.e. not specific to Broca’s) intrinsic cortical microstructure before moving on to interconnections between regions. I’m taking time here because it’s important for me to internalize this microcircuit. So here’s the skeletal circuit (Harris et al. 2013), now including main inhibitory neurons (Lee et al. 2010, Ma et al. 2010, Markman et al. 2004, Rudy et al. 2001, 2011). Basket cells reside in layers II through VI, providing wide-area inhibition (axon branching up to 300-700 microns). The Martinotti cells also reside in layers II through VI but more in deep layers, and their axons extend to layer I and spread over a wide area. The function of bipolar cells is less clear, but they disinhibit other inhibitory cells, among other things. 



Amunts K, Zilles K. A multimodal analysis of structure and function in Broca’s region. Grodzinsky & Amunts, ibid. 2006 Mar 24.

Grodzinsky Y, Amunts K, editors. Broca’s region. Oxford University Press; 2006 Mar 24.

Harris KD, Mrsic-Flogel TD. Cortical connectivity and sensory coding. Nature. 2013 Nov 7;503(7474):51-8.

Lee S, Hjerling-Leffler J, Zagha E, Fishell G, Rudy B. The largest group of superficial neocortical GABAergic interneurons expresses ionotropic serotonin receptors. The Journal of Neuroscience. 2010 Dec 15;30(50):16796-808.

Ma WP, Liu BH, Li YT, Huang ZJ, Zhang LI, Tao HW. Visual representations by cortical somatostatin inhibitory neurons—selective but with weak and delayed responses. The Journal of Neuroscience. 2010 Oct 27;30(43):14371-9.

Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. Interneurons of the neocortical inhibitory system. Nature Reviews Neuroscience. 2004 Oct 1;5(10):793-807.

Rudy B, Fishell G, Lee S, Hjerling‐Leffler J. Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Developmental neurobiology. 2011 Jan 1;71(1):45-61.

Rudy B, McBain CJ. Kv3 channels: voltage-gated K+ channels designed for high-frequency repetitive firing. Trends in neurosciences. 2001 Sep 1;24(9):517-26.


Tuesday, October 25, 2016

Introducing ... Broca's area

So far I’ve looked at general cortical circuits, not specifically at language regions. Today I’ll take a closer look at one of more specifically language related areas: the Broca’s area. Broca’s area deserves a special attention not only because of historical reasons but also because of the clear left-right asymmetry. The Broca’s area expands Brodmann’s cytoarchitectural Areas (BA) 45 (anterior) and 44 (posterior). This 45/44 division roughly corresponds to Economo’s cytoarchitectural division FDG/FCBm and neuroanatomical regions PTr/POp (Pars Triangularis / Pars Opercularis).

Both BA45 and BA44 have leftward volumetric asymmetry, and the asymmetry is affected by handedness (Foundas et al. 1998). The volume fraction of cell bodies in areas 44 and 45 (Amunts et al. 2003) and the size of layer III pyramidal neurons in area 45 (Hayes and Lewis 1995) are shown to be greater on the left side. There are extensive horizontal connections in supragranular layers (I-III) and to a lesser extent in infragranular layers (Tardif et al. 2007). Compared to the visual cortex, there are less connections from infragranular layers to supragranular layers (Tardif et al. 2007).  These two facts (horizontal and inter-layer) may suggest extensive topological processing in the feature space [according to my imagination].

BA45 is characterized by a larger and more uniformly granular layer IV compared to BA44, which is characterized by a dysgranular layer IV invaded by numerous pyramidal neurons (Brodmann 1909). Since BA45 is more granular than BA44, it is predicted that feed forward connection tends to originate more from supragranular neurons in BA45 and terminates in infragranular layers in BA44. It is also predicted that feedback connection tends to originate more from infragranular neurons in BA44 and terminates in supragranular layers in BA45.




Adams RA, Shipp S, Friston KJ. Predictions not commands: active inference in the motor system. Brain Structure and Function. 2013 May 1;218(3):611-43.

Amunts K, Schleicher A, Ditterich A, Zilles K. Broca's region: cytoarchitectonic asymmetry and developmental changes. Journal of Comparative Neurology. 2003 Oct 6;465(1):72-89.

Barrett LF, Simmons WK. Interoceptive predictions in the brain. Nature Reviews Neuroscience. 2015 Jul 1;16(7):419-29. -> Barbas et al. diagram “cortical layer infragranular supragranular M2 M1 connection flow”

Brodmann K. Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Barth; 1909.

Foundas AL, Eure KF, Luevano LF, Weinberger DR. MRI asymmetries of Broca's area: the pars triangularis and pars opercularis. Brain and language. 1998 Oct 1;64(3):282-96.

Hayes TL, Lewis DA. Anatomical specialization of the anterior motor speech area: hemispheric differences in magnopyramidal neurons. Brain and language. 1995 Jun 30;49(3):289-308.

Tardif E, Probst A, Clarke S. Laminar specificity of intrinsic connections in Broca's area. Cerebral Cortex. 2007 Dec 1;17(12):2949-60.
  

Brain Grain

In the last blog I described the canonical six layer cortical structure. That was intentionally a very simplified description. For one thing, the cortical layers include multitudes of cell types the distribution of which differ among different areas. There certainly should be non-systematic variances among brain regions that are shaped by evolution. However, one systematic citoarchitectonic variation in the brain is granularity, ranging from granular (clear layer IV and dense neurons) to dysgranular to agranular (lacking layer IV). The first figure below shows the granularity distribution in the human brain (Beul and Hilgetag 2015, based on Economo 2009). In the sensory modality, granularity seems to decrease as the paths move from the primary to association to higher order association cortices. In the motor modality, it may seem the opposite, as granularity increases from primary to association to higher association cortices. This however is also natural, since in the sensory modality the primary neural pulse propagates from sensory organs, whereas in the motor modality the primary neural pulse propagates to motor organs.

There have been some important observations made in terms of inter-layer connection patterns. One is that the cortico-cortical connectivity pattern in terms of the source and target layers differs depending on the difference of granularity between the source and target areas in non-human primates (Barbas 1986, Barbas and Rempel-Clower 1997). When the granularity difference is large, the connections go either from neurons in the shallow layers of the higher granularity area to shallow layers in the lower granularity area, or to the opposite direction (Figure 2). When granularity difference is small, the source and destination layers are more distributed along the depths. Also, it is observed in the rodent cortex that there are less inter-laminar inhibitory connections in less granular regions (Beul and  Hilgetag 2015). More specifically, in the most granular area (striate), there is inhibition V/VI->(IV and II/III), IV->II/II. In a less granular area (somatosensory), less long-range inhibition to the shallow layer, thus V/VI->IV, IV->(II/III and V/VI). In agranular area (primary motor), no clear inhibitory interlaminar connections were found.

So this sounds simple enough, but just in case you’re itching to hear more about neural modeling at this point, Beul and  Hilgetag (2015) presented neural models based on literature survey on inter- and intralaminar connections as well as prior modeling efforts. In an agranular, rodent frontal cortex model (right column in Figure 3), there are recurrent interlaminar connections V/VI<->II/III and intralaminar inhibitory connections. In a granular, cat striate cortex model (left column in Figure 3), there are linked interlaminar loops VI->IV->V->VI  and VI->IV->II/III->V->VI, intralaminar inhibitions, plus interlaminar inhibitions V->II and IV->II. These recurrent connections may serve amplification, gain control, and normalization (Beul and  Hilgetag 2015).

Fig 1. Granularity gradient

Fig 2. Between-area connectivity patterns

Fig 3. Within-area connectivity models (left:granular area, right: granular area)


References

Barbas H. Pattern in the laminar origin of corticocortical connections. Journal of Comparative Neurology. 1986 Oct 15;252(3):415-22.

Barbas H, Rempel-Clower N. Cortical structure predicts the pattern of corticocortical connections. Cerebral Cortex. 1997 Oct 1;7(7):635-46.

Beul SF, Hilgetag CC. Towards a “canonical” agranular cortical microcircuit. Frontiers in neuroanatomy. 2015 Jan 14;8:165.


von Economo C. Cellular structure of the human cerebral cortex. Karger Medical and Scientific Publishers; 2009.